Assignments
- Research design
Chapter 3 (§3) Introduction: 3.2, 3.4, 3.6, 3.7, 3.8
§3.1: 3.13, 3.14 (or diagram the experiment in 3.13), 3.16 (use Excel), 3.20, 3.25, 3.28
§3.2: Replicate example 3.25; 3.53, 3.61, 3.73
§3.4: 3.99, 3.100, 3.102, 3.110
- Data summaries & displays [If you don't have the text's data CD, you can click on the live links below to download the necessary data sets. Let me know if any of these links point to the wrong data.]
Go through the Beginner's Tutorial for JMP (under Help).
§1 Introduction: Be sure you can do exercises 1.1 & 1.2.
§1.1: Use JMP or Excel to create the bar graph and pie chart in Fig. 1.3 from data on p. 6;
- use JMP to create Fig. 1.4 from data eg01-004 on MM's CD;
- use JMP to create a matched pair of box & whiskers plots for the data in Table 1.2 (ta01-002 or ta01-002rev). What stories can you tell from your plot?
-1.5 (by hand and with JMP ex01-005), 1.6, 1.7 (double click on the scale to change it), 1.8, 1.9, 1.10, 1.12, 1.17, 1.18 (ex01-018), 1.21, 1.34 (ex01-034)
§1.2: Be sure you can do 1.47, 1.48, 1.49, 1.50, 1.51, and 1.52 "by hand." Check with JMP or Excel. Note all the summary statistics appear in Analyze > Distribution under Quantiles (medians, quartiles, etc.) and Moments (mean, standard deviation).
- 1.61 (by hand [median = middle; quartiles are medians of upper and lower halves], 1.63 (ta01-005), 1.65, 1.69
§1.3 - skip
End of chapter 1 exercises: 1.160 (ex01-060).
.
- Scatterplots, regression and correlation as data displays and summaries
§2.1: Replicate Example 2.6 (sctterplot of SAT scores eg02-006) – use JMP's Graph builder (or Analyze > Fit Y by X). Note in the data link I'm giving you here the data is correct. On the MM&C CD, several of the columns are incorrectly identified as categorical data. If you want to see what I did to fix this, bring up the CD data set and click on a column heading to bring up a dialog box to change "character" to "numeric" and "nominal" to "continuous."
- 2.9, 2.12, 2.14 (ta01-002).
- 2.25 (ta02-003) ( Ignore "separate symbols"; use Graph > Overlay Plot with year on the X-axis and record on the Y-axis, and Grouping by sex. Click on the red triangle in the graph, select Overlay Plots > Overlay Groups to merge the two graphs into one. Connecting the points shows the two patterns nicely. Compare the graphs and tell the story (stories) they tell.
§2.2: 2.30 (ex02-030), 2.31 (ex02-031). (Use Analyse > Multivariate methods > Multivariate to show the corrleations and scatterplots. Comment on the scatterplot patterns and the size of the correlations.)
- 2.42 (Use File > New > New Data Table to create a JMP data set with these x's and y's. Proceed as above. After you've seen what the text wants you to see, click on the outlier and tell JMP to exclude that row, and tell JMP to repeat the analysis (red triangle > Script > Redo Analysis). Comment on how the plot and correlation change.
- 2.45 (Find data set ex02-045 and proceed as in 2.30 and 2.31. Use Row > Exclude to repeat the analysis without the outlier.)
§2.3: 2.57, 2.59 (use Fit Y by X in JMP), 2.63, 2.67 (ex02-067 use Fit Y by X in JMP for part (a).The "up and over" lines the text refers to are the lines that go up from x = 2 to the regression line and over to the y-value of that point on the regression line. Find R-squared in the regression print-out.)
§2.4: 2.85 (ex02-085 Use Fit Y by X with Fit Line. For part (c), click on the red triangle beside Linear Fit and select Plot Residuals
- 2.96 (ex02-096 You can compute the correlations in part (b) just by finding the square root of R-squared and putting on the correct sign.)
- Two-way tables [It will be easiest to do these two-way table analyses using Excel (or some other spreadsheet) rather than JMP.]
§2.5: In these exercises you are using bar charts to help tell stories about the data.
- 2.111 [Just type in this data in an Excel spreadsheet (the text's Excell file for this data is not arranged like the table in the the statement of 2.111 and is not very helpful); for part (c) use a bar (or column) chart],
- 2.112 [to display this distribution, you don't have to make a new chart -- you can just use the chart set up for 2.111 and ask for a stacked bar chart],
- 2.113 [here again, you can use the same chart and tell Excel to "sort by" rows -- I found the command in the "chart data" part of the formatting palette]
- 2.120 [in (a) show a chart of some sort that helps get across your description]
§2.6:
2.123, 2.126 [don't be put off by the "challenge" mark; you can do think this through, and it's important], 2.128, 2.133, 2.134
- Case: Presenting data - See class web page called Cases
- Proportions and sample means
§5.1:
5.22, 5.23, 5.24, 5.33 [(c) and (d) are for experts]
§5.2:
5.36, 5.37 [on p. 338], 5.42, 5.48, 5.56, 5.57
- Confidence intervals
§8.1 Proportions:
8.11, 8.14 [for (b), Compute a confidence interval and see if it overlaps with (a); ignore the sentence about "P-value"]
8.17 [ignore the "Challenge" label -- should be do-able], 8.18
8.32
§8.2: Comparing two proportions
Read pp. 505-509 (We won't cover comparing two proportions in class).
Do 8.41 using the method in this section, e.g., Example 8.9. Redo 8.14 using the method in 8.2 for comparing two proportions.
§6.1: Means
6.10, 6.13, 6.15, 6.19, 6.26, 6.31
- Hypothesis testing
§6.2:
6.50, 6.51, 6.52, 6.55, 6.56, 6.58, 6.59, 6.64
6.68, 6.71, 6.73
§6.3:
6.86, 6.6.87, 6.89, 6.92, 6.95, 6.96
- Case: Polling
- Analysis of two-way tables (chi-square and crosstabs)
§9.1 & 9.2
Exercises begin on p. 548: 9.7 (can you still do these graphs!?), 9.9, 9.12, 9.20, 9.35
- Regression
§10.1 & 10.2
Exercises begin on p. 594: 10.6, 10.8, 10.9, 10.10, 10.11, 10.13, 10.22, 10.47
- Case: Visual air quality standards
- Multiple regression
- Case: Air pollution and mortality in U.S. cities