### Statistics Weekly Discussion Assignment

Statistics Weekly Discussion Assignment

Week 1 Statistics DQ
• Statistical power
• Central limit theorem (CLT)
On the basis of your research and understanding, respond to the following:
• Find and state the definition of statistical power that you identify with.
• State the definition of statistical power in your own words.
• Compare and contrast type I and type II errors.
• Explain how power is affected by sample size.

• Find and state the definition of CLT that you identify with.
• State the definition of CLT in your own words.
• Summarize the basic assumptions underlying hypothesis testing and confidence interval methods.
• Explain how these assumptions are affected by sample size.
• Explain the relation of a sample size to the basic assumptions underlying biostatistical analysis. Statistics Weekly Discussion Assignment

Week 2 DQ
Research the following statistical topics:
• Levels of measurement
• Parametric and nonparametric methods
On the basis of your research and understanding, respond to the following:
• Find and state the definition of levels of measurement that distinguishes the five types of data used in statistical analysis.
• In your own words, compare the five types of data and explain how they differ.
• Find and state a definition of parametric and nonparametric methods that distinguishes between the two.
• In your own words, explain the difference between parametric and nonparametric methods.
• Explain which types of data require parametric statistics to be used and which types of data require nonparametric statistics to be used and why. Statistics Weekly Discussion Assignment
• Compare the advantages and disadvantages of using parametric and nonparametric statistics.
• Describe how the level of measurement helps determine which of these methods to use on the data being analyzed.
Statistics Weekly Discussion Assignment
Week 3 DQ
Research the following statistical topics:
• Contingency tables
• The chi-square
• Fisher\'s exact test (FET)
On the basis of your research, respond to the following:
• Find and state a definition of a contingency table that you feel is easy to understand.
• In your own words, explain what contingency tables are and what they are used for.
• Explain what type of data is displayed in contingency tables.
• Explain how contingency tables and their related statistics are used to test for significance of relations among the data.
• Two statistics that can be used in contingency tables are chi-square and FET. Distinguish between the two statistics.
• Explain when you would use the chi-square and when you would use the FET.
• Explain how you would interpret each statistic. Statistics Weekly Discussion Assignment

Week 4
Coefficient of Determination
The purpose of this assignment is to learn about the coefficient of determination (R2) statistic as a measure of the fit of a regression line.
R2 is a statistical measure of how close the data are to a fitted regression line. In general, the higher the R2, the better the model fits your data. However, while R2 measures goodness of fit, it does not indicate whether a regression model is adequate. You can have a low R2 value for a good model or a high R2 value for a model that does not fit the data. Statistics Weekly Discussion Assignment
On the basis of your research and your involvement in public health functions, respond to the following:
• Find and state a definition of R2 that you feel is easy to understand.
• In your own words, provide a substantive explanation of what R2 represents.
• Explain what the statistic R2 is used for in regression analysis.
• Explain how R2 is affected by sample size.
• Describe whether a large R2 value means that a regression is significant. Provide reasons for your answer.
• Describe how you would substantively interpret R2. Statistics Weekly Discussion Assignment

Week 5
ORs and RRs
This assignment will help you analyze the relationship of risk (of an illness) to exposure in public health regression analyses. Both ORs and RRs can be used to demonstrate the relationship between exposure and risk. However, each has its own advantages and disadvantages. While ORs are often used in professional papers, they are also often mistaken for RRs. RRs would often be the better choice as they are less complex than ORs and the interpretation is straightforward. Statistics Weekly Discussion Assignment