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Quantitative Data Analysis using SPSS
Rating: 4.4 out of 5(25 ratings)
75 students

Quantitative Data Analysis using SPSS

Career oriented courses for data analysts
Last updated 5/2021
English

What you'll learn

  • Basic to advanced statistics
  • IBM SPSS software
  • Statistical analysis in SPSS
  • Quantitative business statistics

Course content

9 sections28 lectures4h 57m total length
  • Introduction to SPSS Data Editor8:47

    Know the key features of IBM SPSS Statistics 26 Data Editor. Also get familiar with different menu commands of SPSS data editor.

  • Introduction to measurement scales11:10

    Learn about different measurement scales used in survey research. Understand their features, how to design and use those scales in survey instrument.

  • Defining variables in SPSS13:53

    Learn how to define variables in SPSS using SPSS Variable View option. This lecture explains defining variables with real life questionnaire of international finance corporation.

  • Entering data in SPSS4:33

    Learn how to enter data in SPSS data editor.

  • Editing Data in SPSS: Rename, Recode, Compute9:21

    Learn how to edit data in SPSS data editor. Get familiar with edit options, transform menu, recoding of variables, and performing statistical calculations in SPSS.

Requirements

  • Interest in Statistics, Data Analysis, Data Science
  • Interest in quantitative statistics

Description

This course starts with introduction to basic concepts of statistics with primary focus on quantitative statistics methods. This is the right course for all those who are interested to churn large volume of quantitative data to derive meaningful information.

Next, we introduce you the award-winning statistical software i.e., IBM SPSS. You will learn from basics to most advanced procedures of IBM SPSS.

Then, we teach you different techniques of quantitative statistical methods. These techniques will help you analyze univariate, bivariate and multivariate statistical analysis tools.

We teach all these methods / procedures with the help of SPSS. The advantage of SPSS is that you don't need to write any complex programs or codes to run complicated statistical procedures. Instead of focusing on coding you can focus on defining the tests, run the analysis, and interpret the results.

We also provide the datasets for you to practice the concepts learned from our lectures.

Using the datasets provided and by following video lectures you will learn how to detect univariate outliers, multivariate outliers, t-tests (one sample, related, independent), bivariate analysis like correlation, zero-order correlation, simple linear regression, then multivariate analysis like multiple linear regression. In addition, you will learn bivariate logistic regression, multivariate logistic regression, and finally you will learn analysis of variance (ANOVA).

Who this course is for:

  • Statistics students
  • MBA & BBA students
  • Researchers
  • Looking for career in Data Analytics