1. Analyzing Data Over Time - Part 1 Analyzing Data Over Time Part 1, Slide 1Copyright © 2004, Jim Schwab, University of Texas at Austin

2. Predicting the Future - 1 An essential part of managing any social agency is planning and preparing for the future. This requires that we make some effort to estimate or forecast the future activities of the agency. This week, we will look at quantitative strategies for forecasting using Excel. Before proceeding, we should point out that quantitative forecasting is only one type of forecasting and only works for a limited range of problems, such as estimation of population and stable economic indicators. There are many future issues not amenable to quantitative forecasting, most notably the stock market. Non- quantitative forecasting is often based on the collection of knowledgeable experts who have shown success at being correct in the past. Quantitative forecasting requires that we have some numeric, historical data for the event we want to predict, referred to as a time- series. The forecasting task is to find a trend line that fits or models the historical data, and use that trend line as a basis for predicting the event in the future. Analyzing Data Over Time Part 1, Slide 2Copyright © 2004, Jim Schwab, University of Texas at Austin

3. Predicting the Future - 2 There are many more complicated methods for forecasting, such as econometric models which attempt to predict future events based on complex interactions. In this exercise, we will first forecast the Consumer Price Index or CPI which is used to adjust governmental payments such as social security using a linear trend line. The second example in this exercise will examine a non-linear trend line for predicting population growth, specifically the growth of the population in Texas. Analyzing Data Over Time Part 1, Slide 3Copyright © 2004, Jim Schwab, University of Texas at Austin

4. Navigate to the Bureau of Labor Statistics Home Page The Consumer Price Index is stored on a web site at the Bureau of Labor Statistics. Type in the URL for the Consumer Price Indexes Home Page: http://stats.bls.gov. The Consumer Price Index is stored on a web site at the Bureau of Labor Statistics. Type in the URL for the Consumer Price Indexes Home Page: http://stats.bls.gov. Analyzing Data Over Time Part 1, Slide 4Copyright © 2004, Jim Schwab, University of Texas at Austin

5. Navigate the link for the Consumer Price Index Click on the link for the Consumer Price Index. Analyzing Data Over Time Part 1, Slide 5Copyright © 2004, Jim Schwab, University of Texas at Austin

6. Navigate the link for detailed CPI statistics Click on the link Get Detailed CPI Statistics to go to the web page that enables us to access the data. Analyzing Data Over Time Part 1, Slide 6Copyright © 2004, Jim Schwab, University of Texas at Austin

7. Navigate the link for the CPI statistics (current series) Click on the link All Urban Consumers (Current Series) on the list of most current series. Analyzing Data Over Time Part 1, Slide 7Copyright © 2004, Jim Schwab, University of Texas at Austin

8. Select the data series: U.S. All Items, 1982-84=100 Mark the check box for U.S. All Items, 1982-84=100, to obtain the data for the CPI indexed to 100 during the time period between 1982 and 1984. Analyzing Data Over Time Part 1, Slide 8Copyright © 2004, Jim Schwab, University of Texas at Austin

9. Retrieve the desired data Scroll down the web page until you see the Retrieve data button. Click on the Retrieve data button. Analyzing Data Over Time Part 1, Slide 9Copyright © 2004, Jim Schwab, University of Texas at Austin

10. The link to specify data request Click on the link More Formatting Options to specify exactly what data we would like. Analyzing Data Over Time Part 1, Slide 10Copyright © 2004, Jim Schwab, University of Texas at Austin

11. The specifications for the data First, using the popup menus, change the year range from 1991 to 2003. Second, select Annual Data as the time period that we want. We will specify two changes to get the exact data that we want. Analyzing Data Over Time Part 1, Slide 11Copyright © 2004, Jim Schwab, University of Texas at Austin

12. The specifications for type of output Second, we can paste both HTML tables and text tables into Excel. For this exercise we will copy and paste the HTML table, so we accept the default output as an HTML table. Third, click on the Retrieve Data button to see the final result. First, scroll down the page until you see the Retrieve Data button. Analyzing Data Over Time Part 1, Slide 12Copyright © 2004, Jim Schwab, University of Texas at Austin

13. Copy the output to the clipboard First, scroll down the page until you see the two columns of data: Year and Annual. The annual column contains the annual average CPI index. Second, drag select the two columns of data. Third, select the Copy command from the Edit menu to copy the data to the clipboard. Analyzing Data Over Time Part 1, Slide 13Copyright © 2004, Jim Schwab, University of Texas at Austin

14. Paste the CPI data into Excel Open a new Excel workbook. Click on the Paste tool button on the Standard tool bar. The CPI data is now available as data in Excel. Analyzing Data Over Time Part 1, Slide 14Copyright © 2004, Jim Schwab, University of Texas at Austin

15. Save the CPI data as an Excel Workbook To rename the workbook and save it in a directory where we can later find it, we complete the specifications in the Save As dialog box. We will name the workbook CPI.xls and save it as an Excel file on our computer’s hard drive. Analyzing Data Over Time Part 1, Slide 15Copyright © 2004, Jim Schwab, University of Texas at Austin

16. Remove the web formatting from the table To remove the web formatting (colors and fonts) from the cells, select the cells A1 through B14 and choose the Clear > Formats command from the Edit menu. Analyzing Data Over Time Part 1, Slide 16Copyright © 2004, Jim Schwab, University of Texas at Austin

17. Delete the entry for 2003 from the table Clear the value for 2003 from the table. This is the value that we will forecast. Right click on cell B14 and select Clear Contents from the popup menu. We note the actual value of 184, which we can compare to our predicted value. Clear the value for 2003 from the table. This is the value that we will forecast. Right click on cell B14 and select Clear Contents from the popup menu. We note the actual value of 184, which we can compare to our predicted value. Analyzing Data Over Time Part 1, Slide 17Copyright © 2004, Jim Schwab, University of Texas at Austin

18. Format the table First, substitute the title CPI for the web header for the CPI data. Bold and center both column headers. First, substitute the title CPI for the web header for the CPI data. Bold and center both column headers. Second, format all of the numbers in the CPI column to have 1 decimal place. Third, put outside borders around cells A1 through B1, cells A1 through A14, and cells B1 through B14. Analyzing Data Over Time Part 1, Slide 18Copyright © 2004, Jim Schwab, University of Texas at Austin

19. Create chart for CPI by year First, select the data for the chart, cells A2 through B13. Second, open the Chart tool bar and select the XY (Scatter) Chart as the type of chart to create. After the basic scatter chart has been created, close the Chart tool bar. We will use a line chart to show the average progress for each review period. Though Excel has a chart type called a Line chart, we will use the XY (Scatter) chart. Analyzing Data Over Time Part 1, Slide 19Copyright © 2004, Jim Schwab, University of Texas at Austin

20. Position the chart Move the chart so that its top, left corner is in the upper left corner of cell C1. Analyzing Data Over Time Part 1, Slide 20Copyright © 2004, Jim Schwab, University of Texas at Austin

21. Resize the chart Resize the chart on the worksheet by dragging its handles. Analyzing Data Over Time Part 1, Slide 21Copyright © 2004, Jim Schwab, University of Texas at Austin

22. Add lines to connect the data points The default XY (Scatter) chart does not connect the data points with lines. We will change the chart type to add the lines. Right click on the chart area, and select Chart Type from the popup menu. Analyzing Data Over Time Part 1, Slide 22Copyright © 2004, Jim Schwab, University of Texas at Austin

23. Make chart scatter with data points connected by lines In the Chart Type dialog box, click on the thumbnail sketch of a scatter chart with data points connected by lines. Click on the OK button to change the chart type. Analyzing Data Over Time Part 1, Slide 23Copyright © 2004, Jim Schwab, University of Texas at Austin

24. Remove the legend from the chart To remove the legend from a chart, right click on the legend and select Clear from the popup menu. We have only one series of data on the chart, so we do not need the legend, which does not really contain any useful information on its own. Analyzing Data Over Time Part 1, Slide 24Copyright © 2004, Jim Schwab, University of Texas at Austin

25. Add a title to the chart and to the axes Right click on the chart and select Chart Options from the popup menu. Click on the Titles tab. Right click on the chart and select Chart Options from the popup menu. Click on the Titles tab. First, click in the Chart title text box and type Consumer Price Index, 1991-2002 as the chart title. After a slight delay, Excel adds the chart title to the thumbnail sketch of the chart. Second, select the Value (X) axis text box and type Year. Third, select the Value (Y) axis text box and type Consumer Price Index. Analyzing Data Over Time Part 1, Slide 25Copyright © 2004, Jim Schwab, University of Texas at Austin

26. Add data labels to the points To add data labels, double click on one of the points to open the Format Data Series dialog box, and mark the check box for Value on the Data Labels tab. Analyzing Data Over Time Part 1, Slide 26Copyright © 2004, Jim Schwab, University of Texas at Austin

27. Reduce the size of the title font Select the chart title and reduce the size of the text to 12 point Bold Arial. Analyzing Data Over Time Part 1, Slide 27Copyright © 2004, Jim Schwab, University of Texas at Austin

28. Reduce the size of the title font for the axes Select the vertical axis title and reduce the size of the text to 10 point Bold Arial. Select the horizontal axis title and reduce the size of the text to 10 point Bold Arial. Analyzing Data Over Time Part 1, Slide 28Copyright © 2004, Jim Schwab, University of Texas at Austin

29. Format the font for the data labels and axes Format the data labels and the labels on both axes so that they are displayed in 8 point, Arial Bold. Analyzing Data Over Time Part 1, Slide 29Copyright © 2004, Jim Schwab, University of Texas at Austin

30. Clear the plot area background color and grid lines Right click on the Plot Area of the bar chart and select Clear from the popup menu. This will clear the gray background color from the plot area. Right click on a grid line and select Clear from the popup menu. This will clear the grid lines from the plot area. Right click on the Plot Area of the bar chart and select Clear from the popup menu. This will clear the gray background color from the plot area. Right click on a grid line and select Clear from the popup menu. This will clear the grid lines from the plot area. Analyzing Data Over Time Part 1, Slide 30Copyright © 2004, Jim Schwab, University of Texas at Austin

31. Position value labels above data points Double click on one of the data points to open the Format Data Labels dialog box. Click on the Alignment tab to navigate to that panel. Select Above on the Label Position drop down list. Click on the OK button to re-position the labels. Analyzing Data Over Time Part 1, Slide 31Copyright © 2004, Jim Schwab, University of Texas at Austin

32. The chart with repositioned data labels The data labels are positioned above the plot line, but are not readable because of the limited chart space. We will alternate the data labels so that every other one is above and below the line. The data labels are positioned above the plot line, but are not readable because of the limited chart space. We will alternate the data labels so that every other one is above and below the line. Analyzing Data Over Time Part 1, Slide 32Copyright © 2004, Jim Schwab, University of Texas at Austin

33. Select the second data label in the series Select the second data label. Click once on the label to select all data labels. Click a second time on the second data label to select it individually. Select the second data label. Click once on the label to select all data labels. Click a second time on the second data label to select it individually. Analyzing Data Over Time Part 1, Slide 33Copyright © 2004, Jim Schwab, University of Texas at Austin

34. Change the label position to below the line With the second label selected, right click on it and select Format Data Labels from the popup menu, and select the Alignment tab in the Format Data Labels dialog box. Change the Label Position from Above to Below. Click on the OK button to apply the change. Analyzing Data Over Time Part 1, Slide 34Copyright © 2004, Jim Schwab, University of Texas at Austin

35. The chart with the second data label below the line The second data label is now positioned below the line. Repeat these steps for the fourth, sixth, eighth, tenth, and twelfth data labels. The second data label is now positioned below the line. Repeat these steps for the fourth, sixth, eighth, tenth, and twelfth data labels. Analyzing Data Over Time Part 1, Slide 35Copyright © 2004, Jim Schwab, University of Texas at Austin

36. The chart with data labels above and below the line When we are finished, the label for every other point is above or below the line. Analyzing Data Over Time Part 1, Slide 36Copyright © 2004, Jim Schwab, University of Texas at Austin

37. Add a trendline to the chart Right click on one of the data points and select Add Trendline from the popup menu. Analyzing Data Over Time Part 1, Slide 37Copyright © 2004, Jim Schwab, University of Texas at Austin

38. Complete the add trendline dialog box First, the default Linear trendline is the one we want to add to the chart, so we accept the default. Second, we click on the OK button. Analyzing Data Over Time Part 1, Slide 38Copyright © 2004, Jim Schwab, University of Texas at Austin

39. The trend line on the line chart The trend line is drawn as a straight black line through the middle of the data points, obscuring the line connecting the data points. In this chart, the trend line is not really obvious, so we will change its color. The trend line is drawn as a straight black line through the middle of the data points, obscuring the line connecting the data points. In this chart, the trend line is not really obvious, so we will change its color. First, double click on the trend line to open the Format Trendline dialog box. Analyzing Data Over Time Part 1, Slide 39Copyright © 2004, Jim Schwab, University of Texas at Austin

40. Change the color of the trendline First, click on the Patterns tab where color selection is located. Second, click on the Color drop down palette. Third, click on the Bright Green color swatch (fourth row, fourth from left). Fourth, click on the OK button to apply the color. Analyzing Data Over Time Part 1, Slide 40Copyright © 2004, Jim Schwab, University of Texas at Austin

41. The line chart with a trend line The linear trend line fits the pattern of the data very closely. We can use a linear trend to compute the forecast of the CPI for 2003. Analyzing Data Over Time Part 1, Slide 41Copyright © 2004, Jim Schwab, University of Texas at Austin

42. Forecasting the CPI for 2003 We will use Excel's function wizard to create the FORECAST function. First, select cell B14 as the destination where we will store the result of the FORECAST function. Second, select the Function command from the Insert menu. Analyzing Data Over Time Part 1, Slide 42Copyright © 2004, Jim Schwab, University of Texas at Austin

43. Locate the forecast function by searching We will search for the FORECAST function. The FORECAST function name will appear in the Select a function list box. Click on the OK button access the dialog box where the function arguments are entered. First, type FORECAST in the Search for a function text box. Second, click on the Go button. Analyzing Data Over Time Part 1, Slide 43Copyright © 2004, Jim Schwab, University of Texas at Austin

44. The arguments to the forecast function - 1 The second argument to the FORECAST function is the Known_y's, which are the known CPI figures, in cells B2 through B13. The first argument to the FORECAST function is the X, or year for which we want to estimate the CPI. The year for which we want a forecast is 2003, in cell A14. Analyzing Data Over Time Part 1, Slide 44Copyright © 2004, Jim Schwab, University of Texas at Austin

45. The arguments to the forecast function - 2 The third argument to the FORECAST function is the Known_x's, which are the years for which we have known CPI figures, in cells A2 through A13. Click on the OK button to compute the function. Analyzing Data Over Time Part 1, Slide 45Copyright © 2004, Jim Schwab, University of Texas at Austin

46. The forecast for CPI for 2003 The forecast for 2003 using a linear trend method is approximately 183.9. A forecast of 183.9 compares favorably to the actual value for 2003 of 184.0, indicating that the linear forecast matches the data well. The forecast for 2003 using a linear trend method is approximately 183.9. A forecast of 183.9 compares favorably to the actual value for 2003 of 184.0, indicating that the linear forecast matches the data well. Analyzing Data Over Time Part 1, Slide 46Copyright © 2004, Jim Schwab, University of Texas at Austin

47. Add a discussion text box at the base of the chart To add a discussion text box for the line chart, click on the Text Box tool button and click an insertion point at the base of the chart. Type the text in the text box: Based on a linear relationship between Year and CPI, the estimated CPI for 2003 is 183.9. The chart for the forecasting the with a linear trend is now complete. Analyzing Data Over Time Part 1, Slide 47Copyright © 2004, Jim Schwab, University of Texas at Austin

48. Forecasting a non-linear time series Forecasting with a linear trend line is not always the best model for predicting the future. For example, the growth in a population may not follow a linear pattern. As a population grows, the rate of change is often increasing as new generations produce their own children. In addition, a country or state may experience a steady inflow of immigrants or new citizens who accelerate the change in population. The pattern in population growth may fit what Excel refers to as a growth curve, i.e. the rate of change from year to year increases over time. This is characteristic of the population growth in Texas, and many other areas of the south, where in-migration has added to the increase in the native population. In this situation, an exponential curve may provide a better tool for forecasting future estimates. We use data for the Texas population found at a web site created by the Texas State Libraries and Archives Commission to chart Texas population growth over time. We will compare the results we would obtain with a forecast based on a linear trend line to a forecast based on an exponential trend line. Analyzing Data Over Time Part 1, Slide 48Copyright © 2004, Jim Schwab, University of Texas at Austin

49. Web site with Texas population data Navigate to the Texas State Libraries and Archives Commission web page that lists US and Texas populations by typing in the URL as shown in the address box. Analyzing Data Over Time Part 1, Slide 49Copyright © 2004, Jim Schwab, University of Texas at Austin

50. Locate Official U.S. Census Count and Estimate First, scroll down the web page to locate the table for the Official U.S. Census Count and Estimate. Second, select all of the text in the population table. Third, select the Copy command from the Edit menu. Analyzing Data Over Time Part 1, Slide 50Copyright © 2004, Jim Schwab, University of Texas at Austin

51. Paste the clipboard into the worksheet We want to copy the data table on the clipboard to our Excel worksheet. First, select cell A1 in a new workbook as the destination for the table. Second, click on the Paste tool button. The table is pasted into the worksheet. Analyzing Data Over Time Part 1, Slide 51Copyright © 2004, Jim Schwab, University of Texas at Austin

52. Save the data as an Excel Workbook To rename the workbook and save it in a directory where we can later find it, we complete the specifications in the Save As dialog box. We will name the workbook TexasPopulation.xls and save it as an Excel file on our computer’s hard drive. To rename the workbook and save it in a directory where we can later find it, we complete the specifications in the Save As dialog box. We will name the workbook TexasPopulation.xls and save it as an Excel file on our computer’s hard drive. Analyzing Data Over Time Part 1, Slide 52Copyright © 2004, Jim Schwab, University of Texas at Austin

53. Replace data missing in D and E There are two time periods, 1970 on row 79 and 1980 on row 89, in which the table entries for columns D and E are missing. We will replace these missing entries with the data in columns B and C. First, scroll down to the cells missing data in columns D and E, e.g. row 79. Second, copy the data in cells B79 and C79 and paste it into cells D79 and E79. Third, copy the data in cells B89 and C89 and paste it into cells D89 and E89. Analyzing Data Over Time Part 1, Slide 53Copyright © 2004, Jim Schwab, University of Texas at Austin

54. Delete extraneous columns B, C, and E We do not need the data in columns B, C, and E, so we delete them from the worksheet, leaving only the Year column and the Texas Census column. Analyzing Data Over Time Part 1, Slide 54Copyright © 2004, Jim Schwab, University of Texas at Austin

55. Delete extraneous rows 1-2 and 4-8 from worksheet Some of the rows, 1 through 2 and 4 through 8, are not needed for this exercise, so they are deleted. Analyzing Data Over Time Part 1, Slide 55Copyright © 2004, Jim Schwab, University of Texas at Austin

56. Remove the web formatting from the table To remove the web formatting (colors and fonts) from the cells, select the cells A1 through B105 and choose the Clear > Formats command from the Edit menu. Analyzing Data Over Time Part 1, Slide 56Copyright © 2004, Jim Schwab, University of Texas at Austin

57. Format the population data First, select the cells with the population data: B2 through B105. Second, click on the Comma Style tool button to add comma separators to the population numbers. Third, click on the Decrease Decimal tool button twice to eliminate the decimal and trailing zeros added by the comma formatting. Analyzing Data Over Time Part 1, Slide 57Copyright © 2004, Jim Schwab, University of Texas at Austin

58. Format the table First, substitute the title Year for the web header for the YEAR data. Bold and center both column headers. First, substitute the title Year for the web header for the YEAR data. Bold and center both column headers. Second, put outside borders around cells A1 through B1, cells A1 through A105, and cells B1 through B105. Analyzing Data Over Time Part 1, Slide 58Copyright © 2004, Jim Schwab, University of Texas at Austin

59. Delete the entry for 2003 from the table Clear the value for 2003 from the table. This is the value that we will forecast. Right click on cell B105 and select Clear Contents from the popup menu. We note the actual value of 22,118,509, which we can compare to our predicted value. Clear the value for 2003 from the table. This is the value that we will forecast. Right click on cell B105 and select Clear Contents from the popup menu. We note the actual value of 22,118,509, which we can compare to our predicted value. Analyzing Data Over Time Part 1, Slide 59Copyright © 2004, Jim Schwab, University of Texas at Austin

60. Create chart for population by year First, select the data for the chart, cells A2 through B104. Second, open the Chart tool bar and select the XY (Scatter) Chart as the type of chart to create. After the basic scatter chart has been created, close the Chart tool bar. We will use a line chart to show the average progress for each review period. Though Excel has a chart type called a Line chart, we will use the XY (Scatter) chart. Analyzing Data Over Time Part 1, Slide 60Copyright © 2004, Jim Schwab, University of Texas at Austin

61. Position the chart Move the chart so that its top, left corner is in the upper left corner of cell C1. Analyzing Data Over Time Part 1, Slide 61Copyright © 2004, Jim Schwab, University of Texas at Austin

62. Resize the chart Resize the chart on the worksheet by dragging its handles. Analyzing Data Over Time Part 1, Slide 62Copyright © 2004, Jim Schwab, University of Texas at Austin

63. Add lines to connect the data points The default XY (Scatter) chart does not connect the data points with lines. We will change the chart type to add the lines, even though there are so many data points that they appear to follow a line. Right click on the chart area, and select Chart Type from the popup menu. Analyzing Data Over Time Part 1, Slide 63Copyright © 2004, Jim Schwab, University of Texas at Austin

64. Make chart scatter with data points connected by lines In the Chart Type dialog box, click on the thumbnail sketch of a scatter chart with data points connected by lines. Click on the OK button to change the chart type. Analyzing Data Over Time Part 1, Slide 64Copyright © 2004, Jim Schwab, University of Texas at Austin

65. Remove the legend from the chart To remove the legend from a chart, right click on the legend and select Clear from the popup menu. We have only one series of data on the chart, so we do not need the legend, which does not really contain any useful information on its own. Analyzing Data Over Time Part 1, Slide 65Copyright © 2004, Jim Schwab, University of Texas at Austin

66. Add a title to the chart and to the axes Right click on the chart and select Chart Options from the popup menu. Click on the Titles tab. Right click on the chart and select Chart Options from the popup menu. Click on the Titles tab. First, click in the Chart title text box and type Texas Population, 1900-2002 as the chart title. After a slight delay, Excel adds the chart title to the thumbnail sketch of the chart. Second, select the Value (X) axis text box and type Year. Third, select the Value (Y) axis text box and type Population. Analyzing Data Over Time Part 1, Slide 66Copyright © 2004, Jim Schwab, University of Texas at Austin

67. Reduce the size of the title font Select the chart title and reduce the size of the text to 12 point Bold Arial. Analyzing Data Over Time Part 1, Slide 67Copyright © 2004, Jim Schwab, University of Texas at Austin

68. Reduce the size of the title font for the axes Select the vertical axis title and reduce the size of the text to 10 point Bold Arial. Select the horizontal axis title and reduce the size of the text to 10 point Bold Arial. Analyzing Data Over Time Part 1, Slide 68Copyright © 2004, Jim Schwab, University of Texas at Austin

69. Format the font for the axes labels Format the labels on both axes so that they are displayed in 8 point, Arial Bold. Analyzing Data Over Time Part 1, Slide 69Copyright © 2004, Jim Schwab, University of Texas at Austin

70. Clear the plot area background color Right click on the Plot Area of the bar chart and select Clear from the popup menu. This will clear the gray background color from the plot area. We will not remove the grid lines. With so many data points, we cannot use data labels, so the only means we have for estimating values for any given year is supported by the grid lines. Analyzing Data Over Time Part 1, Slide 70Copyright © 2004, Jim Schwab, University of Texas at Austin

71. Add a trend line to the chart Right click on one of the data points and select Add Trendline from the popup menu. Analyzing Data Over Time Part 1, Slide 71Copyright © 2004, Jim Schwab, University of Texas at Austin

72. Complete the add trend line dialog box First, the default Linear trend line is the one we want to add to the chart, so we accept the default. Second, we click on the OK button. Analyzing Data Over Time Part 1, Slide 72Copyright © 2004, Jim Schwab, University of Texas at Austin

73. The trend line on the line chart The trend line is drawn as a straight black line through the middle of the data points. Because the actual population data fits more of a curved pattern, using the trend line to forecast future population would result in our underestimating the future population Moreover, the farther we try to estimate in the future, the larger will be the underestimate. Analyzing Data Over Time Part 1, Slide 73Copyright © 2004, Jim Schwab, University of Texas at Austin

74. Change the type of the trend line We will try another type of trend line to see if we can obtain a pattern that better fits the historical data. Double click on the trend line to open the Format Trendline dialog box. Analyzing Data Over Time Part 1, Slide 74Copyright © 2004, Jim Schwab, University of Texas at Austin

75. Select the exponential trend line First, click on the Type tab in the Format Trendline dialog box. The thumbnail sketched for the Power and the Exponential trend lines are more similar to the shape of the curve on our population chart. We will use the exponential function because it is commonly used to represent increases in populations which grow at an increasing rate over time. The thumbnail sketched for the Power and the Exponential trend lines are more similar to the shape of the curve on our population chart. We will use the exponential function because it is commonly used to represent increases in populations which grow at an increasing rate over time. While the Format Trendline dialog box is available, we will change the appearance of the trend line after changing its type. Analyzing Data Over Time Part 1, Slide 75Copyright © 2004, Jim Schwab, University of Texas at Austin

76. Change the color and weight of the trend line First, click on the Patterns tab where color selection is located. Second, click on the Color drop down palette and select the Red color swatch. Third, click on the Weight drop down arrow and select the thickest line available, the last one in the list. Fourth, click on the OK button to change the trend line. Analyzing Data Over Time Part 1, Slide 76Copyright © 2004, Jim Schwab, University of Texas at Austin

77. The line chart with an exponential trend line The red exponential trend line fits the pattern of the population data points much more closely than did the linear trend line. We would expect our estimate for future population to be much more accurate based on this trend line. The Excel function which calculates the numeric forecast corresponding to an exponential trend line is the GROWTH function. Analyzing Data Over Time Part 1, Slide 77Copyright © 2004, Jim Schwab, University of Texas at Austin

78. Forecasting Texas Population for 2003 We will use Excel's function wizard to create the GROWTH function. First, select cell B105 as the destination where we will store the result of the GROWTH function. Second, select the Function command from the Insert menu. Analyzing Data Over Time Part 1, Slide 78Copyright © 2004, Jim Schwab, University of Texas at Austin

79. Locate the growth function by searching We will search for the GROWTH function. The GROWTH function name will appear in the Select a function list box. Click on the OK button access the dialog box where the function arguments are entered. First, type GROWTH in the Search for a function text box. Second, click on the Go button. Analyzing Data Over Time Part 1, Slide 79Copyright © 2004, Jim Schwab, University of Texas at Austin

80. The arguments to the growth function - 1 The first argument to the GROWTH function is the Known_y's, which are the known population figures, in cells B2 through B104. The second argument to the GROWTH function is the Known_x's, which are years for which we have known population figures, in cells A2 through A104. Analyzing Data Over Time Part 1, Slide 80Copyright © 2004, Jim Schwab, University of Texas at Austin

81. The arguments to the growth function - 2 The third argument to the GROWTH function is the New_x's, or year for which we want to estimate the population. The year for which we want a forecast is 2003, in cell A105. The final argument to the GROWTH function is a true/false value that tells Excel how to calculate the function. We use TRUE to do the normal calculation of the constant in the equation. Click on the OK button to compute the function. Analyzing Data Over Time Part 1, Slide 81Copyright © 2004, Jim Schwab, University of Texas at Austin

82. The forecast for Texas population for 2003 The forecast for 2003 using an exponential trend method is approximately 21,532,216 people. A forecast of 21,532,216 is an underestimate of 2.7% of the actual value for 2003 of 22,118,509, indicating that the exponential forecast matches the data reasonably well, certainly more accurately than an estimate based on a linear trend line. The forecast for 2003 using an exponential trend method is approximately 21,532,216 people. A forecast of 21,532,216 is an underestimate of 2.7% of the actual value for 2003 of 22,118,509, indicating that the exponential forecast matches the data reasonably well, certainly more accurately than an estimate based on a linear trend line. Analyzing Data Over Time Part 1, Slide 82Copyright © 2004, Jim Schwab, University of Texas at Austin

83. Add a discussion text box at the base of the chart To add a discussion text box for the line chart, click on the Text Box tool button and click an insertion point at the base of the chart. Type the text in the text box: An exponential function was used with data from the years 1900 to 2002 to forecast that the Texas population in 2003 would be 21,532,216 people. The chart for forecasting the with an exponential trend is now complete. Analyzing Data Over Time Part 1, Slide 83Copyright © 2004, Jim Schwab, University of Texas at Austin