4. Are you satisfied with the outcome? Why or why not? Offer a solution and make a new graph (Figure 2).

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1 Assignment 1 Introduction to Excel and SPSS Graphing and Data Manipulation Part 1 Graphing (worksheet 1) 1. Download the BHM excel data file from the course website. 2. Save it to the desktop as an excel workbook file. If you have Excel at home you will also need to save the file in this format. Please remember to save your work on your flashdrive before leaving the lab. 3. Open the file in Excel with worksheet #1. The data displays September climate data for Birmingham from Under the Insert tab, make one graph that best displays September Tmax for each year You will probably have to experiment with several different types. The color schemes, patterns, background, and aesthetics are up to you. Style points are rewarded, but all graphs should reflect a level of simplicity (you don t want to distract from the meaning). Please label your axes and titles and use an appropriate font. Make sure to type a figure caption on your assignment for every figure (Figure 1). 4. Are you satisfied with the outcome? Why or why not? Offer a solution and make a new graph (Figure 2). Part 2 Pivot Table A Pivot Table is an efficient way to summarize large datasets and better understand your data. Make a pivot table (insert tab see above) and answer the following questions.

2 Using the field list, place Year in the column field and Tmax in the data items area. Summarize the mean temperature by year. Use Year as your column heading and Tmax as your data variable. Right click on the first box in your data. Scroll down to where it says field settings. Change the field settings to average and you should get something that looks like this. Now you have instantly summarized average September Tmax for each year. Click on the Pivot Chart button and make a graph of your choice for these results (Figure 3). Now let us play around with the precipitation data. Press the clear button and select clear all. Now you have a fresh pivot table. If your fields are no longer visible, click the field list button. Instead of using

3 Year as the column header, change it to Day and then use Precip in the data field. Right click and go to field settings again. Click on Sum. What is the pivot table displaying? Do you find anything odd about the distribution of the precip data? Make a pivot table graph of your choice to display the data (Figure 4). Hit the clear button again. Arrange the data to answer the following questions. What is the chance of a single day exceeding 90 degrees in September? What is the chance of a Tmin below 50 degrees? What is the chance of a single day without rain? PART III. SPSS Open SPSS and under the File tab click Open< Data. Locate the Excel file from the desktop (you will need to close Excel if it is already running). Once in SPSS there are 2 tabs on the bottom of the page. Click on variable view and change the fields to Numeric if they are not by default. Change the Precip field to Numeric with 2 decimal places. Since you have been making graphs in Excel try and make a graph of your choice (Figure 7) using the Precip data in SPSS under the Graphs tab. Graphs in SPSS have more options but are not necessarily more visually appealing than Excel. Describe your experience with SPSS graphing.

4 Manipulating your data in Excel and SPSS is a vital process before performing any analysis. Under the Data tab there are many options for manipulating and transforming your data. In order to become familiar with these options, let us experiment with a few. Under Data< Sort Cases Use the Precip variable and arrange the data to be sorted by Precip in descending order. Take a screen capture and paste in into your report (Figure 8) as seen below. You should have the most extreme September precipitation days from the last 5 years. Suppose you wanted to focus on extreme precipitation. There are a few ways to do this. First go to Data< Select Cases and then click on the option that says< If Condition is Satisfied. Under this option Type in the following expression. Select Precip and move it into the box and use this expression Precip > 0.5. Now you have filtered out all days where precipitation was less than 0.5 inches and any analysis will be restricted to only the extreme precip days. Take a screen capture (Figure 9). Suppose you wanted to do more a more complex comparison of extreme precipitation in further research. You may need to recode your data. First under Select Cases choose select all to remove the previous filter from above. Then click on clear to manually delete the filter in your spreadsheet. Under Transform< scroll down to Recode Into Different Variables. Select Precip and then under Output Variable use the new name Recode. Your screen should resemble this.

5 Click on Old and New Values. Under Range, change the precip values into 6 categories; 1 10 =1, = 2, = 3, = 4, = 5, 0 = 6 and click continue. Your screen should resemble the following. Under Output Variable click on Change. Then Click OK and take a screen capture (Figure 10). You have transformed the raw precip data into categorical data. A transformation may be appropriate when your dataset is very large with numerous outliers.

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