The top 20 SPSS courses you need to take

1. SPSS Beginners: Master SPSS

4

(615)

Course DescriptionThis SPSS data analysis course was created for one reason, which is to help anyone without statistics or mathematics background to analyze data in SPSS, choose the right descriptive statistics technique and write up the result of the findings with confidence. The course covers everything from entering data into SPSS to interpreting the result and offers easy step-by-step guide to mastering descriptive statistics in SPSS. Firstly, we will take you through the SPSS interface, how to work the system and avoid some of the mistakes people make when choosing variable types and format in SPSS. After that, we will dive into entering data into SPSS, sorting, editing and removing data, and most importantly how to transform any variable into a new variable with recode functions. We will then focus on descriptive statistics in SPSS and you will learn how to run the major descriptive statistics like Mean, Median, Mode, Standard Deviation and One-Samples t-test etc. You will learn how to create graphs, plots and charts in SPSS and how to manipulate them to suit your needs. Finally, we teach you the most important skill that most students wish they had; How to choose the appropriate statistical technique to analyze data in SPSS. We have broken down choosing the right test in SPSS into 3 simple steps: What is your research question?What is the type of variable and how many do you have?What is the level of measurement of your variables?Using the three steps above, you will be able to choose the right test to use to analyze your data and we also use the flow chart to choose the right test for 20 real-life research question examples. Upon completing this course, you will know when to use the following inferential statistic techniques: Pearson CorrelationSpearman Ranked Order CorrelationKendall's Tau B CorrelationIndependent Samples T-testPaired Samples T-testPoint Bi-Serial CorrelationMann Whitney U TestKruskal Wallis Mcnemar's TestChi SquareLinear RegressionMutiple RegressionBinary Logistic RegressionRepeated Measures ANOVABetween Subject ANOVAMixed/Split-Plot ANOVAand so much more. Course MaterialsWe use a mix of video materials, slides, template documents, SPSS data and output files to make sure this course is delivered effectively. Taking this course is perhaps going to be the best decision you will ever make if you are going to use SPSS. It is not just about the content and context, it is more to do with the way the course is delivered and our ability to debunk complicated techniques. Our philosophy is; if you can't explain it simply, you don't understand it well enough. We explain everything using simple English to make sure you make the most of this course. This course should only take few days, but what you will learn will help you for the rest of your life...

2. SPSS Basics

4.5

(545)

A friendly video course for anybody who wants to get the first notions of  statistical analysis with SPSS. If you are an absolute beginner and don't know anything about SPSS, this course is for you. After completing it, you will know how to create an SPSS data set, how to work with your data (select cases, split files, weigh data etc.), how to summarize and visualize your data with charts and tables, how to compute the statistical indicators for your data series, and also how to perform a couple of statistical tests (the ch-square test for association and the independent samples t test). In a word, you will have a solid idea about how SPSS works and what you can do with it. All that's required from you is basic statistics knowledge (this is not a Statistics 101 course). This course is structured in 27 lectures, covering about 20 topics. For every topic I have prepared practical exercises, so you can consolidate your knowledge and form your skills. You can find the exercises in the PDF files attached to almost every lecture. With this course you can master the basics of SPSS in a few days only (depending, of course, of your learning pace). So. just press the enroll button to start learning now.:)...

3. SPSS Masterclass: Learn SPSS From Scratch to Advanced

4.4

(5,904)

Data is the new frontier of 21st century. According to a Harvard Business Report (2012) data science is going to be the hottest job of 21st century and data analysts have a very bright career ahead. This course aims to equip learners with ability of independently carrying out in-depth data analysis with professional confidence and accuracy. It will specifically help those looking to derive business insights, understand consumer behaviour, develop objective plans for new ventures, brand study, or write a scholarly articles in high impact journals and develop high quality thesis/project work. A good knowledge of quantitative data analysis is a sine qua none for progress in academic and corporate world. Keeping this in mind this course has been designed in such way that students, researchers, teachers and corporate professionals who want to equip themselves with sound skills of data analysis and wish to progress with this skill can learn it in in-depth and interesting manner using IBM SPSS Statistics. Lesson OutcomesOn completion of this course you will develop an ability to independently analyze and treat data, plan and carry out new research work based on your research interest. The course encompasses most of the major type of research techniques employed in academic and professional research in most comprehensive, in-depth and stepwise manner. PedagogyThe focus of current training program will be to help participants learn statistical skills through exploring SPSS and its different options. The focus will be to develop practical skills of analyzing data, developing an independent capacity to accurately decide what statistical tests will be appropriate with a particular kind of research objective. The program will also cover how to write the obtained output from SPSS in APA format. Pre-requisiteA love for data analysis and statistics, research aptitude and motivation to do great research work...

4. SPSS For Research

4.4

(1,839)

Become an expert in statistical analysis with the most extended SPSS course at Udemy: 146 video lectures covering about 15 hours of video! Within a very short time you will master all the essential skills of an SPSS data analyst, from the simplest operations with data to the advanced multivariate techniques like logistic regression, multidimensional scaling or principal component analysis. The good news - you don't need any previous experience with SPSS. If you know the very basic statistical concepts, that will do. And you don't need to be a mathematician or a statistician to take this course (neither am I). This course was especially conceived for people who are not professional mathematicians - all the statistical procedures are presented in a simple, straightforward manner, avoiding the technical jargon and the mathematical formulas as much as possible. The formulas are used only when it is absolutely necessary, and they are thoroughly explained. Are you a student or a PhD candidate? An academic researcher looking to improve your statistical analysis skills? Are you dreaming to get a job in the statistical analysis field some day? Are you simply passionate about quantitative analysis? This course is for you, no doubt about it. Very important: this is not just an SPSS tutorial. It does not only show you which menu to select or which button to click in order to run some procedure. This is a hands-on statistical analysis course in the proper sense of the word. For each statistical procedure I provide the following pieces of information: a short, but comprehensive description (so you understand what that technique can do for you) how to perform the procedure in SPSS (live) how to interpret the main output, so you can check your hypotheses and find the answers you need for your research) The course contains 56 guides, presenting 56 statistical procedures, from the simplest to the most advanced (many similar courses out there don't go far beyond the basics). The first guides are absolutely free, so you can dive into the course right now, at no risk. And don't forget that you have 30 full days to evaluate it. If you are not happy, you get your money back. So, what do you have to lose?...

5. Introduction to SPSS

4.5

(311)

November, 2019Course Description: In this course, an introduction to the SPSS software program is provided. We'll take a look at how to get started in SPSS, including creating variables and entering data. After that, we'll cover creating value labels and entering some basic data. Modifying data files, including adding and sorting variables is then covered. After this, a number of descriptive statistics are covered, including bar graphs, stem and leaf plots, and measures of central tendency. Finally, the course concludes with hypothesis testing, with coverage of the Pearson r correlation coefficient...

6. IBM SPSS Modeler Essentials

4.2

(79)

IBM SPSS Modeler enables you to explore data, identify important relationships that you can leverage, and build predictive models quickly, allowing your organization to base its decisions purely on the insights obtained from your data. With the help of this course, you'll follow the industry-standard data mining process, gaining new skills at each stage, from loading data to integrating results into everyday business practices. Get a handle on the most efficient ways of extracting data from your own sources, preparing it for exploration and modeling. You will be acquainted with the best methods for building models that will perform well in your workplace. Go beyond the basics and get the full power of your data mining workbench using IBM SPSS Modeler with this handy tutorial. About the Author: Jesus Salcedo has a Ph. D. in Psychometrics from Fordham University. He is an independent statistical consultant and has been using SPSS products for over 20 years. He is a former SPSS Curriculum Team Lead and Senior Education Specialist who has written numerous SPSS training courses and trained thousands of users. KEITH MCCORMICK is a career-long practitioner of predictive analytics and data science. He has engaged in statistical modeling, data mining, and mentoring others in the area for more than 20 years. He has particular expertise in helping organizations perform their first predictive analytics project or build their first predictive analytics practice, and has done so in a variety of industries including healthcare, banking, telecommunications, non-profit, direct mail, pharmaceuticals, and retail. Keith is also an established author and speaker with four books in print or under contract. Although his consulting work is not restricted to any one tool, his writing and speaking have made him particularly well known in the IBM SPSS Statistics and IBM SPSS Modeler communities...

7. Customer Analytics in SPSS

4.5

(102)

Learn how to get insights from your customer data, understand your customers deeply and target the right customers with the right products! The SPSS program offers a comprehensive customer analytics tool - the Direct Marketing module. With this tool you can conduct powerful analyses without being an expert in statistics and data analysis. The everyday interactions with your customer generates a high amount of valuable data. The customer marketing analysis is the best solution to transform these data into real knowledge. The goal of this analysis is to get you a precise view of your customers, identify the most profitable groups of customers and send them the most appropriate marketing messages. The Direct Marketing toolkit in SPSS includes six practical analysis procedures. Each of these procedures has its own section in this course. The RFM analysis allows you to classify your customers according to the recency, frequency, and monetary value of their purchases. You can pinpoint your most valuable customers (those who buy often and spend much money), as well as adapt your strategy for each RFM customers (e. g. encourage new customers to buy more, reward good customers with discounts and prizes, re-gain old customers that stopped buying from you etc.) The cluster analysis procedure helps you segment your customers or prospects using their most relevant demographic, economic or behavioral characteristics. In each cluster you will find customers that are similar with eah other and different to the others. You can combine this procedure with other analyses, to identify the segments with the highest RFM values, for example, or to estimate the buying probability in each segment. The customer profiling technique helps you detect the customer groups with the highest response rate, based on the results of previous campaign. This way you can know in advance which customers are more likely to respond to your future offers. In consequence, you can significantly improve the targeting of your future campaigns, reduce campaign costs and increase sales and ROI. Another procedure allows you to identify the responses to your campaign  by postal codes. This is extremely useful for direct mailing campaigns, because you can find out the geographical areas where most of your customers live. You can compare the response rate of each geographical zone to your target rate and decide where to send your future mailing packages so you can maximize your profits. The Direct Marketing module in SPSS also helps you estimate the probability of purchase for each contact in your list, using an advanced prediction analysis method (binomial regression). You can send your future messages only to the prospects who are most likely to buy from you and remove the inactive prospects from your list. Moreover, you can predict the probability of purchasing for new customers, those freshly added to your list. The Control Package Test method allows you to compare the effectiveness of two or more marketing campaigns. This is useful especially when you intend to test existing campaigns against new campaigns. The differences between the campaigns response rates are evaluated using the binomial test. Most of the procedures above use sophisticated statistical analysis techniques to process your data. However, you don't have to be a statistician in order to use them. You can get the results you need with a few clicks only, in a few seconds. This is what you will learn in this course. Every procedure is explained live in SPSS, and the output is interpreted in detail. At the end of each section you can find a couple of practical exercises to strengthen your knowledge.     Join this course today and you will be able to analyze your customer data using state-of-the-art predictive techniques and make informed decisions!...

8. Psychometrics using SPSS and AMOS

4.3

(240)

Psychological Testing is widely used in schools, colleges, companies, and institutions around the world. The entire discipline dealing with construction, validation and standardisation of psychological tests and such other assessment tools is known as psychometrics. Psychometric testing is a big business and many big brands like Pearson, Thomas International, Prometric, Aon Hewitt, Ernst and Young, etc, are deeply involved into it. For Human Resource Managers psychometric skills are must but unfortunately MBA courses do not teach about psychometric testing as it's area of hard core quantitative psychologists. Sadly as per my experiences even many universities offering major in psychology do not train their students in psychometric assessment because quantitative psychology specialisations are not given in many universities. Unfortunately, corporate world is flooded with poor tests without any rigour which reflects in poor hire or improper assessment of abilities.  In this background, the course has been built to impart students with technical skills required to built a good psychometric test from scratch so that they can add real value to the intricate issue of assessing human abilities. Its hands on course and my focus will be on skills part while discussing theory only as much as it is essential.  Join the course now and start making yourself a skilled psychometrician today...

9. SPSS Essentials: Statistics made easy

4.5

(242)

Udemy is changing its pricing structure on April 4th when this course will increase to $20. Save money by buying it for $9 now. How do you feel about statistics? Are you afraid you will pick the wrong test? Or make a mistake in your calculations and misinterpret your data? In short: are you afraid of stats? If so, you've come to the right place! I'm here to demonstrate that your fear of statistics is unfounded. Despite what many people think, you don't need to learn complex mathematical formulae to perform statistical analyses. You just need to learn two things. First, you need to know how to choose the right statistical test. Then, you need to know how to do the analysis in computer software like SPSS so you can draw conclusions from your data. It's that easy! This course will show you how to pick the right statistical test by answering four simple questions about your data and your research methodology. I call these the building blocks of statistical analysis, and it involves no maths at all. Then you'll learn how to use SPSS to do the hard work for you. Even if you've never used SPSS, I'll help you get comfortable with the program. You'll learn how to open SPSS, enter data into the program and save it. Next you'll learn how to use SPSS to obtain descriptive statistics such as the mean, median, mode and frequencies. Then you'll discover how to use SPSS to calculate inferential statistics such as the t-test, correlation, Chi-square, ANOVA and regression. The ability to perform quantitative data analysis is becoming an increasingly important skill for researchers to possess. Adding these skills to your CV will make you more employable and give you the confidence you need to start analysing your data today...

10. IBM SPSS Modeler: Getting Started

4

(365)

IBM SPSS Modeler is a data mining workbench that helps you build predictive models quickly and intuitively, without programming. Analysts typically use SPSS Modeler to analyze data by doing data mining and then deploying models. Overview: This course introduces students to data mining and to the functionality available within IBM SPSS Modeler. The series of stand-alone videos, are designed to introduce students to specific nodes or data mining topics. Each video consists of detailed instructions explaining why we are using a technique, in what situations it is used, how to set it up, and how to interpret the results. This course is broken up into phases. The Introduction to Data Mining Phase is designed to get you up to speed on the idea of data mining. You will also learn about the CRISP-DM methodology which will serve as a guide throughout the course and you will also learn how to navigate within Modeler. The Data Understanding Phase addresses the need to understand what your data resources are and the characteristics of those resources. We will discuss how to read data into Modeler. We will also focus on describing, exploring, and assessing data quality. The Data Preparation Phase discusses how to integrate and construct data. While the Modeling Phase will focus on building a predictive model. The Evaluation Phase focuses how to take your data mining results so that you can achieve your business objectives. And finally the Deployment Phase allows you to do something with your findings...

11. Advanced Data Science Techniques in SPSS

4.5

(196)

Become a Top Performing Data Analyst - Take This Advanced Data Science Course in SPSS! Within a few days only you can master some of the most complex data analysis techniques available in the SPSS program. Even if you are not a professional mathematician or statistician, you will understood these techniques perfectly and will be able to apply them in practical, real life situations. These methods are used every day by data scientists and data miners to make accurate predictions using their raw data. If you want to be a high skilled analyst, you must know them! Without further ado, let's see what you are going to learn… Stepwise regression analysis, a technique that helps you select the best subset of predictors for a regression analysis, when you have a big number of predictors. This way you can create regression models that are both parsimonious and effective. Nonlinear regression analysis. After finishing this course, you will be able to fit any nonlinear regression model using SPSS. K nearest neighbor, a very popular predictive technique used mostly for classification purposes. So you will learn how to predict the values of a categorical variable with this method. Decision trees. We will approach both binary (CART) and non-binary (CHAID) trees. For each of these two types we will consider two cases: the case of response dependent variables (regression trees) and the case of categorical response variables (classification trees). Neural networks. Artificial neural networks are hot now, since they are a suitable predictive tool in many situations. In SPSS we can train two types of neural network: the multilayer perceptron (MLP) and the radial basis function (RBF) network. We are going to study both of them in detail. Two-step cluster analysis, an effective grouping procedure that allows us to identify homogeneous groups in our population. It is useful in very many fields like marketing research, medicine (gene research, for example), biology, computer science, social science etc. Survival analysis. If you have to estimate one of the following: the probable time until a certain event happens, what percentage of your population will suffer the event or which particular circumstances influence the probability that the event happens, than you need to apply on of the survival analysis method studied here: Kaplan-Meier or Cox regression. For each analysis technique, a short theoretical introduction is provided, in order to familiarize the reader with the fundamental notions and concepts related to that technique. Afterwards, the analysis is executed on a real-life data set and the output is thoroughly explained. Moreover, for some techniques (KNN, decision trees, neural networks) you will also learn: How to validate your model on an independent data set, using the validation set approach or the cross-validation How to save the model and use it for make predictions on new data that may be available in the future. Join right away and start building sophisticated, in-demand data analysis skills in SPSS!...

12. SPSS Data Analysis for Beginning Researchers

4.5

(235)

Thank you for checking in SPSS Data Analysis for Beginning Researchers. Who is this course for?As the title implies, this course is for people working on their very first research projects (i. e. beginners / newbies), including but not limited to: Students working on their research papers or dissertationsBeginning researchers with a non-technical backgroundAnyone curious about data analysisWhat is so difficult about data analysis?Many people find data analysis difficult, and with good reasons. Data analysis is difficult because it is not a single discipline. It is multi-disciplinary, which means that it requires integrated knowledge from different fields in order to do it right. Specifically, to conduct data analysis for your research you need: Knowledge in the data analysis software (e. g. SPSS, Excel, R, etc.)Knowledge in statistics conceptsKnowledge in research methodsExperience and skills working with dataWhat you need is not only knowledge in separate fields, but also experience and skills integrating these knowledge together to deal with real life data. However, beginning researchers, by definition, have very little of these knowledge, experience, and skills. For example: You may know how to use the data analysis software, but you don't know what method of analysis to use because you are not familiar with the statistics concepts. You may know some statistics, but you may not know how to calculate the statistics on the computer. You may have knowledge in both statistics and data analysis software, but you are not sure what analysis to conduct in order to fulfill the research needs. You may have knowledge in statistics, software, and research, but you may not have the experience in actually handling data, and you are stuck dealing with practical issues here and there (such as missing and invalid data). There are plenty of textbooks in these different disciplines, but few of them could teach you all these knowledge and skills. The problem is not lack of information. Quite the contrary, the problem is overwhelmingly rich information, so rich that you may not know where to start and how to select, so rich that you may not know how to put them into practice to fulfill your specific needs. How may this course help?This course is designed to be concise and practical. I am not attempting to tell you everything about statistics, SPSS, data analysis, and research - that would make your learning journey unnecessarily difficult. Instead, I am going to guide you, in an structured and practical way, through the minimal set of knowledge and skills you would need to analyze your own data. This course will not make you an expert in statistics, SPSS, data analysis, and research, but it will help you finish your own data analysis. This is to be achieved by the following: Background knowledge. Each section of the course begins with a brief introduction to the minimal set of necessary statistics concepts you need. Practical demonstrations. All the videos are example-based. In each video, I show you how to conduct a practical data analysis task. These tasks are carefully selected from a list of most common analyses that you are likely to conduct. Experience sharing. In addition to statistics and SPSS, I also share a lot of my own experience doing research and data analysis, including how to deal with the most common issues while working with data, avoid the common mistakes and misunderstandings, and work around some annoying bugs in SPSS. Key points. Key points are highlighted throughout the video and also recapped at the end of the videos. Exercise. There is an exercise at the end of each section. This helps you apply what you have learned in the previous videos. There are also questions that prompt you to think deeper about what you are doing. The exercise problems have been used for a few years in my own offline classes so they are proven to be helpful to students. While appropriate, a separate video is dedicated to demonstrating the answers to these exercise problems. References. For those who would like to dig deeper into the statistics concepts, I have included links to useful references for your pursue. So, how may I learn effectively in this course?You may do the following for each section: Watch the videos. Take notes while necessary. Complete the exercise on your own. Knowing is not enough. We must apply! If you forget some of the details, refer back to the previous videos. After attempting the exercise, watch the next video for answers. Watch my steps carefully and compare with yours. In case of any difference, ask yourself which way is better, and why. Last but not least, apply the techniques to your own data. That's all for the introduction. Happy learning!...

13. Logistic Regression in SPSS: A Complete Guide

4.5

(51)

Logistic Regression in SPSS: A Complete Guide for Beginners in the Social SciencesThe only course on Udemy that shows you how to perform, interpret and visualize logistic regression in SPSS, using a real world example, using the quantitative research process. Follow along with me as I talk you through everything you need to know to become confident in using regression analysis in your quantitative research report, dissertation or thesis. Perfect for those studying social science subjects or want to increase their statistical confidence and literacy. What's in the course?Learn what logistic regression is, why it is so useful and why you should consider using it Start to think critically about research questions, hypothesis, finding a dataset and thinking about variables. Follow along with an over-the-shoulder example Learn how to perform a simple logistic regression in SPSS and how to interpret and visualize the findingsLearn how to perform multiple logistic regression in SPSS and make statistical conclusions Don't fall for other courses that are over-technical, math's based and heavy on statistics! This course cuts all that out and explains in a way that is easy to understand! Course outcomesOn completion of the course you will fully understand: What logistic regression analysis is and what is used forLearn how to formulate a research question and hypothesisHow to independently identify what data sources and variables are suitable for regression analysisLearn how to import and clean your data in SPSSBuild your own logistic regression model in SPSSHow to interpret the results of a regression outputInterpret and visualize the findings from your model into your research reportincrease your confidence in using quantitative dataLearn this with a real world social science example, you can follow along with. This is the only course on Udemy that shows you from start to finish how regression analysis can be used in your research report from theory to practice. Why take this course?Logistics regression is a statistical model that is used to predict the probability of a certain outcome or event occurring, when that outcome or event is binary (such as pass/fail, true/false, healthy/sick). Logistic regression is used to describe the likelihood of something happening. Social researchers, social science students and academics are increasingly turning to quantitative methods such as logistic regression in their research because, given the right dataset, gives the opportunity to statistically quantify real world social issues. Regression analysis is used to produce headlines like this: Black people '40 times more likely' to be stopped and searched in UKSchools in poorer areas 4x more likely to have Higher grades downgradedTeens who use e-cigarettes up to 5x time more likely to start smokingProspective employers are increasingly looking for students who are experienced in the social sciences but also are confident in data analysis techniques, like logistic regression. The Nuffield Foundation in the UK has highlighted the shortage of quantitatively-skilled social science students in the labour market and has since offered millions of pounds in funding to UK universities in a bid to increase knowledge in quantitative research methods. Pre-requisitesThis course is aimed at students, professionals and beginners in the field who want to begin using the power of logistics regression with SPSS into their study or work. Please don't be scared about statistics, there is NO math's involved in this course. Prior experience of some other quantitative methods and some use of SPSS would be useful, but it is definitely not essential. A passion for data analysis and research will make the process much more enjoyable! Good level of English and access to SPSS is required...

14. Statistics / Data Analysis in SPSS: MANOVA

4.5

(185)

November, 2019. Multivariate Analysis of Variance, a popular but frequently perplexing procedure in statistics, is used to test two or more groups on two or more dependent variables. Mindful of the frustration and confusion that is often experienced with this procedure, this course was carefully designed by a specialist in quantitative methods (statistics) who has successfully taught MANOVA to graduate students from a variety of different backgrounds. Several students who thought they couldn't understand this procedure were later explaining how they not only understood it, but actually found it to be fun! Specifically, this course takes the viewer step-by-step through running and interpreting a number of different multivariate analyses of variance (MANOVA) in SPSS. Several different examples of MANOVA are covered, including:   MANOVA with 2 Groups (Also Known as Hotelling's T-Squared)   MANOVA with 3 Groups   Post-Hoc Tests for Problems with 3 or More Groups   Two-way MANOVA   Equal Covariance Matrix Assumption of MANOVA Explained Step-by-Step   All tests include a detailed, step-by-step explanation of results, including how to assess the results for significance, with written results provided for each test covered.   Enroll today and be confused by MANOVA no longer!...

15. SPSS for healthcare and life science statistics

3.9

(157)

If you want to analyze your own data or need to work in a research team that uses IBM's SPSS software, then this course is for you. From the import of data, through descriptive statistics, data visualization, correlation, the comparison of means, and the analysis of categorical variables, this course will leave you familiar with the user interface and able to conduct all of the most common statistical tests...

16. SPSS for NonStatisticians- Analysis, Interpretation, Writeup

5

(54)

For students, researchers and data analysts who don't have a strong statistical background (or any statistical background), this course teaches you statistical data analysis, interpretation, and APA reporting in a simple, practical approach. Alexander Mtembenuzeni takes the same simple explanations approach he took with the Learn SPSS in 15 minutes video on YouTube (now with over 1.9 million views and so many great comments) and used it to create this course. The goal of this course is to get you to complete your research project without the need to go through complicated theories! The course takes you from absolute beginner of SPSS and statistics with lessons such as getting familiar with the SPSS interface, creating variables, entering data, and running, interpreting and reporting basic analyses. From there, you will be introduced to inferential tests and hypothesis testing with statistics such as t-tests, ANOVA and linear regressions. The course covers: Data entry, data importing and preparationSummarizing data using descriptive statisticsExploring relationships between different types of variablesChoosing appropriate charts and developing themTransforming variables and managing the data to suit your analysesChoosing the appropriate inferential tests such as chi-square, t-tests and regression and running themHow to interpret all the statistics presented in the course And how to write your results in your reports, dissertations, or thesis using the APA format...

17. Survival Analysis using SPSS, Simplified in Arabic

4.7

(99)

هذا الكورس عبارة عن فيديوهات قصيرة بالعربية والانجليزية لتوضيح الموضوع وطريقة تنفيذه باستخدام البرنامج مع أمثلة توضيحية وملفات للتدريب تغطى الموضوعات التالية:- Survival analysis - Kaplan-Meier curve- Log Rank test- Cox regression- Application using SPSSالكورس يتطلب معرفة بأساسيات الاحصاء ، ومعرفة مسبقة ببرنامج SPSS--إذا لم تكن لديك خبرة سابقة فى استخدام البرنامج ، ستساعدك الفيديوهات على فهم الموضوع ولكن التطبيق قد لا يكون يسيرا لتعلم برنامج SPSS من البداية يمكنك الاشتراك فى الكورس الآخر المخصص لذلك--للمزيد يمكنك تحميل كتابنا فى الإحصاء  Applied Medical Statistics For Beginners.نتمنى لكم خالص الفائدة --Learning Survival analysis is important for those who are studying medical statistics. Survival analysis is concerned with the time until an event occurs (time to event). This event is usually death, as survival after breast cancer, but can be any other event. Examples:· Time from operation to death.· Time from response till the recurrence of a tumour.· Time from operation to discharge from the hospital.--Learning Survival analysis is important for those who are studying medical statistics. Survival analysis is concerned with the time until an event occurs (time to event). This event is usually death, as survival after breast cancer, but can be any other event. Examples:· Time from operation to death.· Time from response till the recurrence of a tumour.· Time from operation to discharge from the hospital...

18. Statistics/Data Analysis with SPSS: Descriptive Statistics

4.5

(1,113)

November, 2019. Get marketable and highly sought after skills in this course that will increase your knowledge of data analytics, with a focus on descriptive statistics, an important tool for understanding trends in data and making important business decisions.   Enroll now to join the more than 2000 students and get instant access to all course content! Whether a student or professional in the field, learn the important basics of both descriptive statistics and IBM SPSS so that you can perform data analyses and start using descriptive statistics effectively.          By monitoring and analyzing data correctly, you can make the best decisions to excel in your work as well as increase profits and outperform your competition.          This beginner's course offers easy to understand step-by-step instructions on how to make the most of IBM SPSS for data analysis.    Make Better Business Decisions with SPSS Data Analysis  Create, Copy, and Apply Value LabelsInsert, Move, Modify, Sort, and Delete VariablesCreate Charts and GraphsMeasure Central Tendency, Variability, z-Scores, Normal Distribution, and Correlation  Interpret and Use Data Easily and Effectively with IBM SPSS          IBM SPSS is a software program designed for analyzing data. You can use it to perform every aspect of the analytical process, including planning, data collection, analysis, reporting, and deployment.          This introductory course will show you how to use SPSS to run analyses, enter and code values, and interpret data correctly so you can make valid predictions about what strategies will make your organization successful.    Contents and Overview          This course begins with an introduction to IBM SPSS. It covers all of the basics so that even beginners will feel at ease and quickly progress. You'll tackle creating value labels, manipulating variables, modifying default options, and more.          Once ready, you'll move on to learn how to create charts and graphs, such as histograms, stem and leaf plots, and more. You'll be able to clearly organize and read data that you've collected.          Then you'll master central tendency, which includes finding the mean, median, and mode. You'll also learn how to measure the standard deviation and variance, as well as how to find the z-score.          The course ends with introductory statistics video lectures that dive deeper into graphs, central tendency, normal distribution, variability, and z-scores.          Upon completion of this course, you'll be ready to apply what you've learned to excel in your statistics classes and make smarter business decisions. You'll be able to use the many features in SPSS to gather and interpret data more effectively, as well as plan strategies that will yield the best results as well as the highest profit margins...

19. Statistics / Data Analysis in SPSS: Inferential Statistics

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November, 2019. Join more than 1,000 students and get instant access to this best-selling content - enroll today! Get marketable and highly sought after skills in this course that will substantially increase your knowledge of data analytics, with a focus in the area of significance testing, an important tool for A/B testing and product assessment. Many tests covered, including three different t tests, two ANOVAs, post hoc tests, chi-square tests (great for A/B testing), correlation, and regression. Database management also covered! Two in-depth examples provided of each test for additional practice. This course is great for professionals, as it provides step by step instruction of tests with clear and accurate explanations. Get ahead of the competition and make these tests important parts of your data analytic toolkit! Students will also have the tools needed to succeed in their statistics and experimental design courses. Data Analytics is an rapidly growing area in high demand (e. g., McKinsey)Statistics play a key role in the process of making sound business decisions that will generate higher profits. Without statistics, it's difficult to determine what your target audience wants and needs.    Inferential statistics, in particular, help you understand a population's needs better so that you can provide attractive products and services.    This course is designed for business professionals who want to know how to analyze data. You'll learn how to use IBM SPSS to draw accurate conclusions on your research and make decisions that will benefit your customers and your bottom line.    Use Tests in SPSS to Correctly Analyze Inferential Statistics  Use the One Sample t Test to Draw Conclusions about a PopulationUnderstand ANOVA and the Chi SquareMaster Correlation and RegressionLearn Data Management Techniques  Analyze Research Results Accurately to Make Better Business Decisions    With SPSS, you can analyze data to make the right business decisions for your customer base. And by understanding how to use inferential statistics, you can draw accurate conclusions about a large group of people, based on research conducted on a sample of that population.    This easy-to-follow course, which contains illustrative examples throughout, will show you how to use tests to assess if the results of your research are statistically significant.    You'll be able to determine the appropriate statistical test to use for a particular data set, and you'll know how to understand, calculate, and interpret effect sizes and confidence intervals.    You'll even know how to write the results of statistical analyses in APA format, one of the most popular and accepted formats for presenting the results of statistical analyses, which you can successfully adapt to other formats as needed.    Contents and Overview    This course begins with a brief introduction before diving right into the One Sample t Test, Independent Samples t Test, and Dependent Samples t Test. You'll use these tests to analyze differences and similarities between sample groups in a population. This will help you determine if you need to change your business plan for certain markets of consumers.    Next, you'll tackle how to use ANOVA (Analysis of Variance), including Post-hoc Tests and Levene's Equal Variance Test. These tests will also help you determine what drives consumer decisions and behaviors between different groups.    When ready, you'll master correlation and regression, as well as the chi-square. As with all previous sections, you'll see illustrations of how to analyze a statistical test, and you'll access additional examples for more practice.    Finally, you'll learn about data management in SPSS, including sorting and adding variables.    By the end of this course, you'll be substantially more confident in both IBM SPSS and statistics. You'll know how to use data to come to the right conclusions about your market.    By understanding how to use inferential statistics, you'll be able to identify consumer needs and come up with products and/or services that will address those needs effectively.  Join the over 1,000 students who have taken this best-selling course - enroll today!...