Correlation and Regression Project
Purpose:
The purpose of this term project is to allow the students to apply data collection, hypothesis testing, estimation and hypothesis testing for population means, analysis of variance, and linear regression analysis methods to solve real world problem or make decisions.
Required Components:
1) Problem Statement
You need to clearly define what problem you want to solve or what kind of business decision you need to make base on the statistical analysis of the data.
2) Null and Alternative Hypothesis
Based on the problem, you need to state the null and alternative hypothesis.
3) Data Collection
To test your hypothesis, you need to sample the data. In data sampling, please indicate what kind of sampling method you used to collect the data, and specify if the data is primary data or secondary data. (For the secondary data, please reference where the data comes from). In addition, what kind of effort you made to avoid bias in data sampling.
4) Data Analysis and Hypothesis Testing
Once data is collected, you need to find a way to analyze it. Please indicate which method you are going to use to test hypothesis (i.e.: estimation and hypothesis testing for population means, analysis of variance, and linear regression).
You need to clearly list the assumption for the hypothesis testing method you are going to use.
For One-way ANOVA as example, the assumptions are:
- Populations are normally distributed
- Populations have equal variances
- Samples are randomly and independently drawn
- Data’s measurement level is interval or ratio
You need to explain how your data met all the required assumptions for your testing method.
Also, you need to list number of factors and interactions, specify the confidence level and etc.
Finally you can use Data Analysis Toolkit in Excel to run the Hypothesis Test.
5) Conclusions/Decision Making
Interpret the Hypothesis Test result. It should include your conclusion and how you arrived at that conclusion with the confidence level you specified in step 4).
