1 Business 90: Business Statistics Professor David Mease Sec 03, T R 7:30-8:45AM BBC 204 Lecture 8 = Finish Chapter Presenting Data in Tables and Charts.

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1 Business 90: Business Statistics Professor David Mease Sec 03, T R 7:30-8:45AM BBC 204 Lecture 8 = Finish Chapter Presenting Data in Tables and Charts (PDITAC) Agenda: 1) Go over quiz on Homework 2 2) Reminder about Homework 3 (due Tuesday) 3) Lecture over rest of Chapter PDITAC

3 Presenting Data in Tables and Charts Statistics for Managers Using Microsoft ® Excel 4 th Edition

4 Chapter Goals After completing this chapter, you should be able to: Create an ordered array Construct and interpret a frequency distribution, histogram, and polygon for numerical data Construct and interpret a cumulative percentage distribution and ogive for numerical data Create and interpret contingency tables, bar charts, and pie charts for categorical data Create and interpret a scatter diagram and a least squares regression line (in other chapter p. 387-398) Describe appropriate and inappropriate ways to display data graphically

5 Graphs and Tables for Two Variables (Bivariate Data) Two Numerical Variables: Scatter Diagram Two Categorical Variables: Contingency Table (also called cross-classification table or two-way table) Side-by-Side Bar Chart

6 Contingency Tables Using Excel Just like with summary tables, to make a contingency table in Excel, it is often useful to use a Pivot Table to count the frequencies of the different categories, especially for large datasets. This is done by selecting Data and then PivotTable and PivotChart Report. Next go to Layout and drag the name of one variable into the row and the other into the column. Pick either one and also drag it into the data area. (Be sure you name the two columns where you have the data first.)

7 Contingency Tables Using Excel

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10 Contingency Tables Using Excel

11 Contingency Tables Using Excel

12 Contingency Tables Using Excel

13 Contingency Tables Using Excel

14 In class exercise #25: The file http://www.cob.sjsu.edu/mease_d/gender_and_major.xls lists the genders and majors for Bus 90 students from a previous term. Make a contingency table using the Pivot Table feature in Excel. Put Gender along the side and major along the top.

15 In class exercise #25: The file http://www.cob.sjsu.edu/mease_d/gender_and_major.xls lists the genders and majors for Bus 90 students from a previous term. Make a contingency table using the Pivot Table feature in Excel. Put Gender along the side and major along the top. ANSWER:

16 Graphs and Tables for Two Variables (Bivariate Data) Two Numerical Variables: Scatter Diagram Two Categorical Variables: Contingency Table (also called cross-classification table or two-way table) Side-by-Side Bar Chart

17 In class exercise #26: Make a side-by-side bar chart for the data from ICE #25 by hand. Put the major along the x-axis and use different colored bars for the two genders.

18 In class exercise #26: Make a side-by-side bar chart for the data from ICE #25 by hand. Put the major along the x-axis and use different colored bars for the two genders. ANSWER:

19 Graphs and Tables for Two Variables (Bivariate Data) Two Numerical Variables: Scatter Diagram Two Categorical Variables: Contingency Table (also called cross-classification table or two-way table) Side-by-Side Bar Chart

20 Scatter Diagrams are used for bivariate numerical data Bivariate data consists of paired observations taken from two numerical variables The Scatter Diagram: one variable is measured on the vertical axis and the other variable is measured on the horizontal axis Scatter Diagrams

21 Scatter Diagram Example Volume per day Cost per day 23125 26140 29146 33160 38167 42170 50188 55195 60200

22 Scatter Diagrams in Excel Select Insert > Chart 1 2 Select XY(Scatter) option, then click Next The data range is the y values and the x values go under the Series tab Important: Dont include column names 3

23 In class exercise #27: The file http://www.cob.sjsu.edu/mease_d/football.xls gives the total number of wins for each of the 117 Division 1A college football teams for the 2003 and 2004 seasons. Use Excel to make a scatter diagram for this data. Put 2003 wins on the x-axis.

24 In class exercise #27: The file http://www.cob.sjsu.edu/mease_d/football.xls gives the total number of wins for each of the 117 Division 1A college football teams for the 2003 and 2004 seasons. Use Excel to make a scatter diagram for this data. Put 2003 wins on the x-axis. ANSWER:

25 Described on pages 387-398 (in a different chapter) It is the line that fits the data the best as determined by minimizing squared vertical differences The coefficient of correlation (r) measures the strength and direction of the linear relationship (positive=up, negative=down) R-squared also measures the strength of the linear relationship, but not the direction The Least Squares Regression Line

26 Scatter Plots of Data with Various Correlation Coefficients Y X Y X Y X Y X r = -1 r = -.6 r = +.3 r = +1

27 Adding the Least Squares Regression Line Using Excel Click once on the graph 1

28 Adding the Least Squares Regression Line Using Excel From the Chart menu select Add Trendline 2

29 Adding the Least Squares Regression Line Using Excel Choose the first choice (Linear) and press OK 3

30 Adding the Least Squares Regression Line Using Excel The line should now appear on your scatter diagram. Double click on the line then under the Options tab check the last two boxes. 4

31 In class exercise #28: A) Graph the least squares regression line for the football data on the scatter diagram using Excel. B) Give the equation of the least squares regression line using Excel. C) What is the slope of the least squares regression line? D) Interpret the slope of the least squares regression line. E) What is the coefficient of correlation? F) What is the value of R-squared? G) Use the least squares regression line to predict the number of 2004 wins for a team that won 12 games in 2003.

32 In class exercise #28: A) Graph the least squares regression line for the football data on the scatter diagram using Excel. ANSWER for Part A:

33 Principles of Graphical Excellence Present data in a way that provides substance, statistics and design Communicate complex ideas with clarity, precision and efficiency Give the largest number of ideas in the most efficient manner Excellence almost always involves several dimensions Tell the truth about the data

34 Using chart junk Failing to provide a relative basis in comparing data between groups Compressing or distorting the vertical axis Providing no zero point on the vertical axis Errors in Presenting Data

35 Compressing Vertical Axis Good Presentation Quarterly Sales Bad Presentation 0 25 50 Q1Q2Q3 Q4 \$ 0 100 200 Q1Q2 Q3 Q4 \$

36 No Zero Point On Vertical Axis Monthly Sales 0 39 42 45 J F MAMJ \$ 36 0 20 40 60 JFM A MJ \$ Good Presentations Monthly Sales Bad Presentation 36 39 42 45 JFMAMJ \$ Graphing the first six months of sales or

37 No Relative Basis Good Presentation As received by students. Bad Presentation 0 200 300 FRSOJRSR Freq. 10% 30% FRSOJRSR FR = Freshmen, SO = Sophomore, JR = Junior, SR = Senior 100 20% 0% %

38 Chart Junk Good Presentation 1960: \$1.00 1970: \$1.60 1980: \$3.10 1990: \$3.80 Minimum Wage 0 2 4 1960197019801990 \$ Bad Presentation

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