In this section, you will use the data for *ONE* variable only. Pick the variable that is more interesting to analyze. For example: if your independent variable is sequential data such as year with 30 years and one piece of data per year, your x-values might be 1971, 1972, 1973, 1974, …, 2000. This would not be interesting to analyze. In that case, choose to use the dependent variable to analyze for this part of the project.

**_____** Summarize your data in a chart with columns showing data value, frequency, relative frequency, and cumulative relative frequency. **_____** Answer the following, rounded to 2 decimal places:
**1.** Sample mean = **2.** Sample standard deviation = **3.** First quartile = **4.** Third quartile = **5.** Median = **6.** 70th percentile = **7.** Value that is 2 standard deviations above the mean = **8.** Value that is 1.5 standard deviations below the mean =

**_____** Construct a histogram displaying your data. Group your data into 6 – 10 intervals of equal width. Pick regularly spaced intervals that make sense in relation to your data.
For example, do NOT group data by age as 20-26,27-33,34-40,41-47,48-54,55-61 . . . Instead, maybe use age groups 19.5-24.5, 24.5-29.5, . . . or 19.5-29.5, 29.5-39.5, 39.5-49.5, . . . **_____** In complete sentences, describe the shape of your histogram. **_____** Are there any potential outliers? Which values are they? Show your work and calculations as to how you used the potential outlier formula in chapter 2 (since you are now using univariate data) to determine which values might be outliers. **_____** Construct a box plot of your data. **_____** Does the middle 50% of your data appear to be concentrated together or spread out? Explain how you determined this. **_____** Looking at both the histogram AND the box plot, discuss the distribution of your data. For example: how does the spread of the middle 50% of your data compare to the spread of the rest of the data represented in the box plot; how does this correspond to your description of the shape of the histogram; how does the graphical display show any outliers you may have found; does the histogram show any gaps in the data that are not visible in the box plot; are there any interesting features of your data that you should point out.

Comments:"Reviewer's Comments: 'I recommend this book. Overall, the chapters are very readable and the material presented is consistent and appropriate for the course. A wide range of exercises introduces […]"