STATS 4 DATA

COURSE OUTLINE

MODULE 1

• Introducton to Quantitative Analysis
• Definition of terms
• Types of Data
• Variable Types
• Measurement of Levels
• Hypotheses
• Types of Hypotheses
• Steps for Hypotheses Testing

MODULE 2

• What is Data Analysis
• Steps to analysing data
• Data Preparation
• Outliers
• Normal Distribution Test
• Reliabilty Test

MODULE 3

• Designing a questionnaire
• What is hypothesis?
• What is variable?
• Relationship between hypothesis, objectives, and questionnaires
• Understanding of P-value
• Dependent and Independent variable
• Pilot Research

MODULE 4

• Inferential Statistics
• Chi Square Test
• Conditions/assumptions for using chi-square.
• How to calculate chi square test in Excel
• Analysis of Variance (Anova)
• Types of Anova
• One-way Anova
• Conditions for using one way Anova
• Two ways Anova
• Difference between Two ways Anova with replication and without replication
• Conditions for using two way Anova
• Correlation
• Pearson r correlation
• Types of research questions a Pearson correlation can examine
• Conditions for using correlation
• Method for getting correlation.

MODULE 5

• T Test
• Different types of T test
• One Sample T Test
• When to use one sample T test
• Conditions/ Assumptions for using One Sample T test
• How to perform one sample t test in excel
• Dependent Sample T test
• When to use dependent sample T test
• Conditions/ Assumptions for using dependent Sample T test
• How to perform dependent sample t test in excel
• Differences between one tailed distribution and two tailed distribution.
• Independent Sample T test
• When to use independent sample T test
• Conditions/ Assumptions for using independent Sample T test
• How to perform independent sample t test in excel
• Regression
• The regression line
• Types of regression
• Assumptions for regression
• Linear Regression
• Assumption for Linear Regression
• How to solve linear regression
• Multiple Regression
• Assumption for multiple Regression
• How to solve multiple regression
• Trend Analysis/ Time series
• When to use tend analysis
• Assumption for trend analysis
• How to solve trend analysis
• How to perform trend analysis.