Fall 2002

Dr. McCullough

MINITAB Assignment Sheet # 1

Due : Monday, September 30, 2002

Instructions : Bring your homework finished to class on the Due Date specified on separate sheet (s) of paper. Clearly label each problem and each part of a problem on your paper. Your homework should be stapled together with your name on each sheet and should not contain fringe from a spiral notebook. Make sure and print information and explain in detail on any questions or comments.

1. ) Simulate a data set and construct the following graphs by performing the following operations :

a. ) Randomly generate a column of data (c1) with 100 entries { Calc\Random Data\Integer }. Minimum number is 0 and maximum number is 5.

b. ) With this data set generate a pie chart. {Graph\PIE Chart}. Data set in C1 .

c. ) With this data set generate a histogram. {Graph\Histogram}. Graph X variable in C1 .

d. ) With this data set generate a dotplot. {Graph\Character Graph\Dotplot}. Variable in C1 .

e. ) Randomly generate a column of data (c2) with 100 entries { Calc\Random Data\Integer }. Minimum number is 0 and maximum number is 50.

f. ) With this data set generate a stem and leaf plot. {Graph\Character Graph\Stem and Leaf}. Data set in C2 .

g. ) With data set generate a box plot. {Graph\Character Graph\BOXPlot}. Data set in C2 .

h. ) With the data set in C2 calculate summary statistics. {Stat\Basic Statistics\Display Descriptive Statistics } Variable C2.

i. ) Calculate the interquartile range, range, midrange, and variance. Check the values from the output against your Boxplot.

j. ) Explain all graphs in detail. Which of these graphs do you think should be used to express each data set to an individual whom does not know what the data set looks like?

2. ) Enter the following data set into two columns in the data window. Keeping the order pairs across from each other. A study was performed on the wear of a bearing, y, and the relationship to oil viscosity, x. The following data were obtained :

y | 193 230 172 91 113 125

x | 1.6 15.5 22 43 33 40

a. ) Calculate the linear regression information. { Stat\Regression\Regression }

b. ) Write the linear correlation coefficient and interpret it.

c. ) Write the line of best fit or regression equation.

d. ) Use the regression equation to predict the wear of a bearing or explain why not if oil

viscosity is 180.

e. ) Use the regression equation to predict the wear of a bearing or explain why not if oil

viscosity is 32.0.