please see attachment,
Before starting this assignment you should know a few things. First, I consolidated each of your datasets into a single data set with all of the cases/respondents in one dataset called the class_survey. I also created several new variables in the dataset: 1. A grouped age variable where each category represents an age range; and, 2. A total score for the BSSS; and, 3. a total score for the ICU. The “BSSTotal” and “ICUTotal” are summed scores of those items on each of the respective scales (in the dataset these are named BSSS1 – BSSS8 and ICU1 – ICU10R, respectively). You will also notice there are several “ICU#R” variables. These are reverse coded ICU items so that when the items are used to compute a total ICU score, they are all in the same direction (i.e., higher callous unemotional traits).
Also, you should know that the BSSS is the Brief Sensation Seeking Scale and the ICU is the Inventory of Callous and Unemotional Traits. You should have some familiarity with scale use from research methods but the basic idea is that each of the items that are included on a scale tap into the same underlying construct. In this case the items tap into Sensation-Seeking and Callous-Unemotional traits, respectively. Sensation-Seeking is defined as being daring, willing to take risks, and being fearless. Callous-Unemotional traits are defined as being callous, uncaring, lacking remorse and guilt and having a lack of emotional expression. The idea is that the more items that individuals endorse at a higher value, the more of these traits an individual has. Thus, these are scales or inventories because the individual items are summed to create a scale that represents the construct (sensation-seeking and callous-unemotional traits). People that score higher have more of the trait that those that score relatively lower. We typically do not use the individual items in this but only the summed scores which we treat as continuous measures (i.e., scale in SPSS). It is important that you understand what these are measuring so that you can discuss your findings in a meaningful way.
Using the class_survey dataset complete the following:
1. In SPSS conduct the appropriate measures of central tendency and dispersion for ALL variables in the classsurvey dataset (except for the individual items of the BSSS and ICU – only compute measures of central tendency for total scores – “ICU” and “BSSS”). Remember to take into consideration the level of measurement when determining which measure of central tendency and dispersion to report.
2. Create a single table in Microsoft Word that reports the descriptive statistics for all of the variables (except the individuals items for the ICU and BSSS – only report on the total scores). Be sure to use names for variables in the table so that a reader would know what you are referring to – sometimes the labels in SPSS are not intuitive. Also, give the table a proper title and label it “Table 1”. If you use any abbreviations make sure to describe what these are in a “note” below the table. See the example provided below.
Note. DO NOT copy and paste the tables from SPSS. You should create a table in word (e.g., insert -> table) that combines all the information from the SPSS output into a single table.
Your table should have columns labeled: Mean/%, SD, minimum, and maximum.
Not all variables will have a value for each column. ONLY REPORT VALUE WHEN APPROPRIATE – e.g, it is not appropriate to report a mean for a nominal variable, in this case you should report the % of each category of the variable.
DO NOT include the individual items that make up the BSSS and ICU – only report on the total scores I created.
3. Write a single paragraph describing the sample regarding the average scores and variation for each variable. Make sure to reference the table that you created in #2 in the text. This should resemble a sample description that you would typically see in a manuscript.
4. In SPSS, create frequency tables in SPSS for the variables “race”, “age_group”, “education” and “BSSSTotal” using the classsurvey dataset. Then create the appropriate graph (e.g., bar chart, pie chart, histogram) for each of these variables.
5. Write a paragraph describing the shape of the distribution of the four variables from #4 based on the frequency table and graphs (you do not have to create tables/graphs to include in your assignment – only include your “write-up”.
Note. Turn in your write-up from #3 and #5 with the table you created from #2 in a word document. Do not turn in your spss output.
Write-up examples:
“As shown in Table 1, a majority of survey respondents identified as Black (67.0%), male(52.2%), and the mean age was 43 years old (SD = 14.29). On average, respondents reported a score of 2.65 (SD = .48) on a measure of social integration and a 1.10 (SD = .99) on the gang proximity scale. At the neighborhood level, the mean for the measure of residential stability was -.01 (SD = .57). Neighborhoods in the sample were on average 67.1% Black. The mean scores for racial heterogeneity and concentrated disadvantage were .27 (SD = .18) and .01 (SD = .74), respectively.” The mean number of gangs per neighborhood was .84 (SD = 1.18).”
