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Curriculum
- 6 Sections
- 25 Lessons
- 16 Weeks
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- Module 1: Introduction to Data Analytics10
- 1.1a. Data Science vs. Data Analytics
- 1.2b. Data Literacy
- 1.3c. Data Types
- 1.4Introduction to Statistics I
- 1.5a. Meaning and understanding of statistics
- 1.6b. Descriptive statistics
- 1.7c. Inferential statistics
- 1.8Introduction to Statistics II
- 1.9a. Parametric Test (In-dept explanations) T-test Pearson correlation Regression Analysis etc.
- 1.10b. Non-Parametric Test (In-dept explanations) Chi-Square Spearman’s rank correlations Kruskal Wallis test etc.
- Data Analysis with IBM SPSS0
- Module 2: Setting Up Data in SPSS5
- 3.1a. Overview of SPSS
- 3.2b. Data Entry In SPSS
- 3.3c. Saving Data In SPSS
- 3.4d. Exploring Data using Descriptive statistics (Mean, Standard deviation, etc.) and exploratory data analysis (Bar Chart, Pie Chart, Histogram, Boxplot, Scatter plot, etc.)
- 3.5e. Analyzing your data using Inferential statistics I (Practical in SPSS) Identify the data Describing the data/Graph Question formulation Setting up hypothesis Checking for normality of the data Selecting appropriate test
- Module 3: Inferential Statistics II-Mean Comparison I (Practical in SPSS)3
- Module: Inferential Statistics III-Predictive Analytics (Practical in SPSS)4
- Module 4: Inferential Statistics IV-Mean comparison II (Practical in SPSS)4