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## Chapter 4 SPSS: Summarising bivariate data

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**Enter the data from Example 4.1 into two columns then click**Variable View. Name the variables Price and Sales. Change the Measure to Scale for both variables. Correlation coefficient**Choose Correlate from the Analyze menu then select Bivariate**from the sub-menu.**In the new window click Price then click the right arrow to**the left of the space under Variables. Repeat the process for Sales. Click OK.**Put the data from Example 4.1 into two worksheet columns and**configure the variables as outlined on slide 2. Simple linear regression**Choose Regression from the Analyze menu and Linear from the**sub-menu.**In the command window click Sales then click the right arrow**to the left of the space under Dependent. Click Price then click the right arrow to the left of the space under Independent(s). Click OK.**The Coefficients table in the Output Viewerhas the intercept**and slope of the line of best-fit in the B column under Unstandardized Coefficients.**The Seasonal Decomposition facility in SPSS requires four**data cycles so enter the sales from Example 4.15 into a worksheet column in chronological order and add the following eight values: 16.4, 38.3, 37.9, 7.5, 17.2, 40.0, 40.5, 8.2. Time series decomposition**Choose Years, quarters under Cases Are.**Below First Case Is: make the Year 1 and the Quarter 1, and check that the Periodicity at higher level is 4.**Click OK and columns of data headed YEAR, QUARTER and DATE**appear in the worksheet.**Select Forecasting from the Analyze menu and Seasonal**Decomposition from the sub-menu.**In the command window move Sales variable to the space below**Variable(s) and select Additive under Model. Click OK.**Four new columns of data appear in the worksheet; ERR (the**errors), SAS (the seasonally adjusted series), SAF (seasonal adjustment factors), and STC (smoothed trend cycle).**For a plot of the series with the trend estimates select**Forecasting from the Analyze menu and Sequence Charts from the sub-menu.**Move Sales and Trend-cycle to the space below Variables and**Date.format to the space below Time Axis Labels. Click OK.