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# Run a frequency distribution on all variables to ensure that nothing was missed. Include the mean, median, and/or mode, and the standard deviation (see lab from last few weeks for how to do that).

You will input your own data today using the survey your instructor administered and analyzed a few years ago for a study on the relationship between trust and willingness to get the HPV vaccine.
STEP ONE: adding the variables

• Start by opening the blank survey “HPV survey” found on Canvas. Go to question # 89. You are going to create a data set by entering variables 89-101.
• Open a blank data set in SPSS. Go to the Variable View and click in the first box under the “Name” column. Name the first variable “gender.” For the rest of the variables, name each of them something that makes sense. There can be no spaces in the variables names. SPSS will auto-fill the rest of the rows with information. The only columns you need to worry about are Width, Decimals, and Values.
• Width is the number of numeric characters before the decimal point, Decimals is after, and Values is how the data will be coded into number. As the “gender” variable will be dichotomous (only 2 response categories), and relating to the survey question about male or female, the Width should be 1 and Decimals at zero.
• Click on the box under the Values column, then the blue icon labeled “…” and a box should pop up. Type “0” into the Value box, “female” into the “label” box and hit Add. Then “1” for “male” and hit OK.
• Do this for the rest of the variables 90-101. Unlike the gender variable, all of the other variables will have more than two responses, so you will need to assign numeric values to each response. For example, for the race/ethnicity question, you could make Hispanic/Latino=0, Asian=1, black=2, American Indian=3, pacific islander=4, white=5, and other=6.

*** For the “year you were born’ question, since you are using actual numbers, not just numbers to code other information, you do not need to assign values to these responses. SPSS will understand the response information just fine.
***For variables that have an “other” response category, just assign the next number to this category. (usually researchers will create a whole other variable for each “other” response, but in the interest of time we are not going to do that)
***For variables that have a “don’t know” response category, assign a value of “99” to this response. In analyzing the data, the researcher will often “throw out” these “don’t knows,” and so to avoid confusion, they often assign it a value that is far from the other values. For example, with the father’s education category, you could have values from 0-4 (or 1-5, either is acceptable) for less than high school through graduate school, and then a 99 for ‘don’t know.’
***For the last question about college major, instead of the variable being “numeric,” in the second column in SPSS under TYPE, choose “string.” You do not need to assign numeric values since there are no response categories. Also, change the width to “20”.
STEP TWO: Inputting the Data

• While still in Variable View, right click on the top box under the blank column to the left of the “Name” column. Click “Insert Variable.” A new row should appear at the top of the spreadsheet labeled “VAR00001.” Click this box and change the name to “case.”
• Switch to Data View. Assign every respondent (all of the 10 completed surveys) a case number. This is merely for clerical purposes and is a good habit to get into for when you work with larger data sets that can easily become disorganized. Much like the age variable, no values need to be assigned for this “variable.”
• On Canvas, find and open the file called “HPV data.” This is the (fictional) data of 10 people who completed the survey. Populate the responses into the spreadsheet. Each respondent will be one row in the spreadsheet.
• Run a frequency distribution on all variables to ensure that nothing was missed. Include the mean, median, and/or mode, and the standard deviation (see lab from last few weeks for how to do that). MAKE SURE YOU LOOK OVER YOUR FREQUENCY DISTRIBUTIONS (You can tell if anything was missed if your variable name is listed as missing, and you have a number value alongside your variable names.) If anything was missed, go back to Variable view and fix it. Copy & Paste the Statistics table and the frequency distributions for all variables 89-101 below. Save this data set; we may use it in later weeks.
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