talked about some statistics are junk , and you have to be careful in how you ask your questions and interrupt the results . STEP 4 : Bar Chart and Summary Statistics Using the BarChart worksheet , calculate the summary statistics shown at the bottom of the data , for each of Bottles , Cans , and Plastic . Create a bar chart to the right of the data , with a title of Marketing Campaign Results . You can choose the colors that you want for each city ' s results , but make sure that you show the Y-axis labels to the right and the X-axis labels on the bottom , along with the word City as their label . STEP 5 : Line Chart Using the LineChart1 worksheet , calculate the average income for the ages listed . Then create a line chart , with a title of Average Income by Age , with appropriate labels on the X and Y axis . Your chart should be placed to the right of your data , on the same sheet . STEP 6 : Average and Median , With Line Chart This step is very similar to the previous worksheet , except that there is an additional summary statistic and you are working with multiple variables . Calculate the average and median for both Income and Rent . As you look at your results , do you notice the difference between the results ? Does this better explain the difference between average and median for you ? To the right of the data , on the same sheet , produce a line graph of the Income and Rent . Again , the color of the lines is your choice . Use a chart heading of Average Income / Rent by Age . Be sure to show your Income and Rent labels to the right of the chart , and a label of Age on the X axis and Amount ($ 000 ) on the Y axis . STEP 7 : Regression Analysis and Scatter Graph The data here is very simple , and not really a good example of using regression analysis , but the process behind the exercise is the most important issue . 1 . Create a scatter chart of the data , below the data , with a title of Revenue Growth . 2 . Draw a trendline associated with the data points . Be sure to select the inclusion of the Equation and R-squared values on the chart .