1. Explain when it is reasonable to draw a causal conclusion about the effects of a treatment used in a study. Why is this the case?

2. Sampling methods are discussed in this section and often students confuse stratified sampling and cluster sampling. What tools will you use to make the distinction between these two sampling methods?

3. Suppose you are given a summary of a study, how will you be able to tell whether the study represents an observational study or an experiment? Explain.

4. When faced with a data set, how will you determine the type of variables presented, i.e. categorical, numerical discrete, or numerical continuous? Be clear and specific in your process for determining the difference

5. what is statistics? Give an example of where/how you have seen statistics used in your life.

6. One aspect of this section is determining numerical values to summarize a distribution, specifically the center and spread of the data. Find a graphical display of data and then state what measure of center and what measure of spread is the best for numerically summarizing this data set and why. Attach a picture of the data .

7. Find or design a contingency table with at least one categorical variable. State the variables in the table and their possible outcomes. Provide an example of a meaningful question that can be asked about the data set. Attach a picture of the contingency table.

8. Give an example of a variable, not a data set, whose outcomes take on either a symmetric shape or skewed shape then discuss why this variable has that specific shape.