Provide a "real-world" example of each of the terms below and explain what makes it an appropriate example of the term. (1 point each)

1. Qualitative variable.
2. Discrete quantitative variable.
3. Continuous quantitative variable.
4. Descriptive statistic. What is the rationale for calling it descriptive?
5. Inferential statistic. What is the rationale for calling it inferential?

Provide an example of how you could use each of the sampling methods below. Explain how each example fits that particular method. (1 point each)

1. Simple Random Sampling
2. Stratified Sampling
3. Cluster Sampling
4. Systematic Sampling
5. Convenience Sampling

In a sentence or two each, provide examples of each of the following terms and explain why the example illustrates the related concept. Do not use examples from the text but use critical thinking to make up your own. (1 point each)

1. Independent events
2. Dependent events
3. Complementary events
4. Union of events
5. Intersection of events

Use an example to describe an appropriate use of each of the chart types below. Just describe the use and do not try to show the chart itself. What is the advantage of using that particular chart type to represent the data? (1 point each)

1. Pie chart
2. Bar chart
3. Histogram
4. Stem and leaf display
5. Box plot

Given a data set that can be graphed as a standard normal curve, respond to the prompts below. (1 point each)

1. What defines the graph? I.e., what determines the shape of the graph and what is the relationship between these defining characteristics?
2. What must be done in order to transform a normal distribution of data into a standard normal distribution based on the same data?
3. What is the advantage of having transformed data so that it can be represented by a standard normal distribution?
4. We often see data points represented by either x or z. What is the relationship between them?
5. Why is the area under the standard normal curve above the mean always the same value?