Results Skeleton

Your Results section will include four sections:

(1) Sample Demographics (1-3 tables; frequencies and/or descriptives)
(2) Dependent Variable(s) (1-2 tables; frequencies and/or descriptives)
(3) Independent Variables (1-3 tables; frequencies and/or descriptives)
(4) Significance test(s) (1-2 tables; correlation, independent samples t-test, and/or crosstab w/chi square tests).

Note: the tables shown below were copy/pasted from Word, and do not come out well in this blog (i.e., they're all smooshed). Refer to the Word document I emailed to everyone for examples of presentable SPSS output tables.

SECTION 1: Sample Demographics



Table 1: Newspapers from which sample comes

 

 

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	New York Times (1)	41	51.3	51.3	51.3
	Los Angeles Times (2)	39	48.8	48.8	100.0
	Total	80	100.0	100.0

As seen in Table 1, the sample was split nearly evenly between articles from the NY Times (51%) and the LA Times (49%).


Table 2: Sample Gender
  

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	male (1)	34	42.5	42.5	42.5
	female (2)	46	57.5	57.5	100.0
	Total	80	100.0	100.0

As seen above in Table 2, my sample heavily consisted of slightly  more female (58%) than male (42%) students. My sample was split about evenly between CJ majors (52%) and non-CJ majors (48%; not shown in table format).


SECTION 2: Dependent Variables

Table 3: Dependent Variable

	N	Minimum	Maximum	Mean	Std. Deviation
Y_Recidivism #: number of mentions of recidivism (dep. var.)	80	0	5	.44	.992
Valid N (listwise)	80

As seen above in Table 3, my dependent variable – number of mentions of recidivism – was mentioned on average .44 times in the newspaper articles. There was a minimum of 0 mentions in one or more articles, and a maximum mention of 5 in 1 or more articles. AND DON’T FORGET TO ADD IN YOUR QUALITATIVE DATA (THE WORDS AND PHRASES). Examples of the words and phrases that mean recidivism are: chronic offender, repeat offenders, did it again, and went on to commit more crime.

Other Table option (for survey question dependent variables)

 Table 3: How many individuals with drug use problem who attempt to stop end up relapsing?

  

 

		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	1 in 10 (1)	36	45.0	45.0	45.0
	1 in 25 (2)	31	38.8	38.8	83.8
	1 in 50 (3)	12	15.0	15.0	98.8
	1 in 100 (4)	1	1.3	1.3	100.0
	Total	80	100.0	100.0

As seen above in Other Table 3, nearly 84 percent of my sample thought that relapse by drug users was fairly common, with either 1 in 10 or 1 in 25 individuals using drugs again. Fifteen percent of my sample felt that only 1 in 50 drug users would relapse, and 1 individual felt that drug relapse was rare (i.e., only 1 in 100 users).


SECTION 3: Independent Variables

Table 4: Independent Variables, Causal Factors of Recidivism

	N	Minimum	Maximum	Mean	Std. Deviation
X1_Age #	79	1	35	9.27	7.074
X2_Race/Ethnicity #	80	0	22	1.03	3.085
X3_Education #	80	0	7	1.46	2.098
X4_Enviorment #	80	0	6	1.33	1.682
X5_Gender #	80	0	17	1.96	3.021
X6_Alt.Program #	80	0	14	1.99	2.848
X7_Violence #	80	0	30	6.39	5.568
Valid N (listwise)	79

As seen above in Table 4, of the independent variables, number of mentions of age and violence appeared the most frequently. Age was mentioned an average of 9 times in one or more articles, with a minimum of 1 mention and a maximum of 35 mentions. Violence was mentioned on average 6 times in the articles. Violence had a minimum of 0 mentions, and a maximum of 30 mentions in 1 or more articles. AND DON’T FORGET TO ADD IN YOUR QUALITATIVE DATA (THE WORDS AND PHRASES) Language used to describe violence included: rape, assault, beatings, violence, abuse, homicide, robbing, and drowning.

SECTION 4: Significance testing for testing your research question or hypothesis)

• Option 1: Correlation (appropriate for 2 continuous variables), OR
• Option 2: crosstab w/chi square (appropriate for 2 categorical variables) OR
• Option 3: independent samples t-test (appropriate for 1 continuous and 1 categorical variable).

You’ll run 1 or 2 of these. Which tests you run will depend on the type of variables you are using, in particular continuous or categorical variables. See this video (skip the add) re: variable types: http://www.youtube.com/watch?v=CNW9txOMYAg.

Recall: Categorical variables have categories of responses, like male/female, yes/no, CNN.com/FoxNews.com, strongly agree…strongly disagree
Continuous variables do NOT have categories of responses; ex: age, number of mentions of whatever (delinquency, joining gangs, family structure, IPV, etc.)

Option 1: Correlation (appropriate for 2 continuous variables); in SPSS, Analyze-Correlate-Bivariate. Click over your continuous variables into the “variables” box, beginning with the dependent variable on top. See also ch. 5 (I think, depending on your edition of the book), “Pearson Correlation Coefficient” in the Cronk SPSS book. Also see this video clip:

		Y_Recidivism #: number of mentions of recidivism (dep. var.)
X1_Age #	Pearson Correlation	-.162
	Sig. (2-tailed)	.153
	N	79
X2_Race/Ethnicity #	Pearson Correlation	-.020
	Sig. (2-tailed)	.859
	N	80
X3_Education #	Pearson Correlation	-.038
	Sig. (2-tailed)	.740
	N	80
X4_Enviorment #	Pearson Correlation	-.018
	Sig. (2-tailed)	.874
	N	80
X5_Gender #	Pearson Correlation	.014
	Sig. (2-tailed)	.902
	N	80
X6_Alt.Program #	Pearson Correlation	.101
	Sig. (2-tailed)	.375
	N	80
X7_Violence #	Pearson Correlation	.070
	Sig. (2-tailed)	.539
	N	80

**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

As seen above in Table 5, a correlation analysis showed that none of my independent variables were significantly related to my dependent variable. I was surprised to learn that recidivism and environment are not related to each other. This is counter to what I hypothesized.

Table 7: Relationship of Number of Offenses, Age, and Alcohol Use

		Y1_NUMBER OF JUVENILE OFFENSES	Y2_NUMBER OF ADULT OFFENSES
X3_RECODE OF AGE AT 1ST OFFENSE	Pearson Correlation	-.626(**)	-.335(**)
	Sig. (2-tailed)	.000	.000
	N	588	588
X4_ALCOHOL INVOLVED IN CRIME	Pearson Correlation	.215(**)	.221(**)
	Sig. (2-tailed)	.001	.001
	N	239	239

**. Correlation is significant at the 0.01 level (2-tailed).

As seen above in Table 7, there were statistically significant relationships between both of my dependent variables - number of juvenile and adult offenses - and both independent variables. Age at first offense was negatively related to both dependent variables, suggesting that the younger the age of beginning criminal involvement, the greater the number of both juvenile and adult offenses. Note that the size of the correlation coefficient was particularly robust (big) for X3 and Y1 (juvenile offenses). Alcohol use during the crime was positively related to both dependent variables, suggesting that the more an offender uses alcohol, the more likely they are to commit a crime. There was also a significant, positive, and non-small (r = .3) relationship between Y1 and Y2, not shown in table format.


Option 2: crosstab w/chi square (appropriate for 2 categorical variables). In SPSS, analyze-descriptives-crosstabs. Click dependent variable into either row or column box, and independent variable into the other box (whatever you didn’t click the dependent variable into). In the “statistics” tab click “chi square” test. In “cells” tab, select row percents. See also Cronk book this is ch. 7 (I think, depending on your edition of the book). See also this video clip.


Table 8: Subject Gender by Treatment or Control Group (Cathy Widom data)

  

			X1_SUBJECT / CONTROL		Total
			Subjects	Controls
X2_CHILD'S GENDER	Female	Count	462	462	924
		% within X1_SUBJECT / CONTROL	52.7%	52.7%	52.7%
	Male	Count	415	415	830
		% within X1_SUBJECT / CONTROL	47.3%	47.3%	47.3%
Total		Count	877	877	1754
		% within X1_SUBJECT / CONTROL	100.0%	100.0%	100.0%

Χ2 = .00, df= 1, p = 1.00 (take this info from the table below, and then you can delete that table)

                                                                         Chi-Square Tests

	Value	df	Asymp. Sig. (2-sided)	Exact Sig. (2-sided)	Exact Sig. (1-sided)
Pearson Chi-Square	.000(b)	1	1.000
Continuity Correction(a)	.000	1	1.000
Likelihood Ratio	.000	1	1.000
Fisher's Exact Test				1.000	.519
Linear-by-Linear Association	.000	1	1.000
N of Valid Cases	1754

a  Computed only for a 2x2 table

b  0 cells (.0%) have expected count less than 5. The minimum expected count is 415.00.

As seen above in Table 8, there was no pattern of difference in which gender was assigned to which experimental group. In fact, identical numbers of females AND males appear in both the treatment (subject) and control groups (e.g., 462 females in both the subject and control groups). Thus, the chi square value is not statistically significant.



Table 9: Marital Status of Male and Female Police Officers

 

			GENDER		Total
			Male	Female
Y1_MARITAL STATUS	Married	Count	601	56	657
		% within GENDER	64.1%	36.4%	60.2%
	Live-in partner	Count	66	22	88
		% within GENDER	7.0%	14.3%	8.1%
	Divorced/Separated	Count	100	34	134
		% within GENDER	10.7%	22.1%	12.3%
	Single	Count	171	42	213
		% within GENDER	18.2%	27.3%	19.5%
Total		Count	938	154	1092
		% within GENDER	100.0%	100.0%	100.0%

Chi square: 45.104, df=3, p= .00

As seen above in Table 9, different marital and cohabitation patterns were evident for male vs. female police officers. Male officers were more likely to be married (64% of the sample of 938 officers), compared with only 36% of the female officers (out the n=154). Female officers were twice as likely to cohabitate with an intimate partner than were male officers (14% vs. 7%, respectively). More female officers were divorced (22%) than were male officers (just under 11%). More female officers were also single (27%) than their male counterparts (18%). The results of the chi square test were statistically significant. These results suggest that policing as a profession may be more detrimental to female officers' personal/romantic life and stability than it (policing) is for male officers. This may be due to... (here you'd speculate, as appropriate to your research question, on why fewer female officers get or remain married... social expectations of wives, etc.)

Option 3: independent samples t-test (appropriate for 1 continuous and 1 categorical variable). In SPSS, analyze-compare means-independent samples t-test. (See also ch. 6 in Cronk SPSS book, depending on your edition of the book). Click the categorical variable (ex: major CJ vs. non-CJ) into the grouping variable box, then “define” the grouping variable as per which number means which response: Ex: group 1 = CJ majors, group 2 = non-CJ majors. In the “test variable” box click over the dependent variable. Click okay to run. See also this video clip.

Table 11: Comparison of Mean Mentions of Recidivism by News Source

  

	NYT-1 LAT- 2	N	Mean	Std. Deviation	Std. Error Mean
Y_Recidivism #: number of mentions of recidivism (dep. var.)	New York Times (1)	41	.68	1.234	.193
	Los Angeles Times (2)	39	.18	.556	.089

 T= 2.33, p= .022

As seen above in Table 11, recidivism and its synonyms were mentioned more frequently in the NYT than in the LA Times. In the NY Times, recidivism was mentioned on average .68 times in the articles, compared with the very low .18 mean mentions in the LA Times. This difference was statistically significant (p=.02) as per the t-test analysis. I also ran a series of t-test analyses of all my independent variables by which news source (NYT or LAT), but none of these were statistically significant.

Table 12: Comparison of Mean Juvenile and Adult Offenses by Subject or Control Group

	X1_SUBJECT / CONTROL	N	Mean	Std. Deviation	Std. Error Mean
Y1_NUMBER OF JUVENILE OFFENSES	Subjects	397	1.63	3.138	.158
	Controls	192	.35	1.097	.079
Y2_NUMBER OF ADULT OFFENSES	Subjects	397	9.24	13.821	.694
	Controls	192	4.43	7.002	.505

Both t-values are statistically significant. Y1: t= 5.48, p= .00; Y2: t=4.55, p= .00

.

As seen above in Table 12, individuals in the "subject" group committed higher mean (average) numbers of both juvenile and adult offenses than did the "control" individuals. The t-test results for both dependent variables were statistically significant. The differences in means for the adult offenses (Y2) were particularly noticeable: a mean of over 9 offenses for the subjects, compared with less than 5 offenses on average for the controls. These findings suggest that the "subject" group - those individuals subjected to severe physical or sexual abuse or neglect in childhood - go on to break the law more than do the non-abused/non-neglected control group.

Research Proposals and Confusion about Dependent Variables

The following blog posting was originally uploaded to my hub here: http://hubpages.com/hub/Research-Proposals-and-Confusion-about-Dependent-Variables

Having taught a year-long, two-course research component to Kean students for the past few years, it has become apparent that one of the most nagging issues for students is the dependent variable. Consider the following:

"My research proposal is about whether the death penalty reduces murder, so my dependent variable would be whether or not states have capital punishment, right?"

Wrong.

Research methods textbooks aren't necessarily helpful. Yes, they give the definition but even when my students do the reading, I can see from the blank stares that what they've read isn't sinking in. Here's a sampling of definitions for dependent variables from a few methods books:

From Singleton & Straits (2010), Approaches to Social Research: "The dependent variable is the one the researcher is interested in explaining and predicting. Variation in the dependent variable is thought to depend on or to be influenced by certain other variables. The explanatory variables that do the influencing and explaining are called independent. If we think in terms of cause and effect, the independent variable is the presumed cause and the dependant variable is the presumed effect."

From Maxfield & Babbie (2011), Research Methods for Criminal Justice and Criminology: "The variable assumed to depend on or be caused by another variable (called the independent variable). If you find that sentence length is partly a function of the number of prior arrests, then sentence length is being treated as a dependent variable."

And from my beloved Bachman & Paternoster (1997) Statistical Methods for Criminology and Criminal Justice: "Dependent variable - the variable that is being affected or influenced by another variable. It is often denoted as y. In a causal analysis the dependent variable is caused by the independent variable."

See a common theme in these definitions? The variables pertain to cause and effect. In the social sciences (like CJ, sociology and psychology), the effects are often people's behavior. In criminal justice field, those behaviors of interest would be..... crime! Crime. Antisocial behavior. Violence. Bad things that people do.

How do we measure our dependent variable crime? There are various ways, including arrests, victimization data (people reporting that they were harmed), and self-report criminal behavior (what people tell you they did criminally, for which they may or may not have been caught).

So to return to the original research question "Does capital punishment reduce crime?" the dependent variable would be crime, specifically states' arrest rates.
Other examples:

(1) Research question: Does the such-and-such conflict resolution program make schools safer?

Dependent variable: measure(s) of school safety such as # of fights, # of times the police are called to a school, # of suspensions for fighting.

(2) Research question: Does Colorado's anti-bullying law reduce bullying in school?

Dependent variable: measure(s) of bullying in school, such as data gathered through surveys of students about whether they've been bullied, done any bullying, or witnessed any bullying

(3) Research question: Does mandatory arrest by police reduce domestic violence (DV)?

Dependent variable: measure(s) of domestic violence reoffending (for instance)

(4) Research question: Which makes neighborhoods safer, having the police drive through the area or walk the beat on foot?

Dependent variable: measure(s) of neighborhood crime, such as home burglaries

Welcome Back! Looking ahead to Fall 2010 Seminar

To my many, many incoming CJ_4600/Senior Seminar students:

Welcome to the course! I look forward to meeting all of you in just over a month. Some of you I already know, either from Research Methods or another course. In any case, welcome, welcome, welcome.

Two words: don't worry.

Senior Seminar is the course many students dread. Why? It's a lot of work. You probably haven't done anything like this - execute a research study - before. You've heard horror stories from other students.

I'll try and reassure you - it'll be fine. Really. You'll live through it. There will be a lot of you, but I try to give each student about 30 minutes of one-on-one time throughout the semester.

Let me give you a quick picture of the shape of the semester. The first four weeks are spent gearing up to submit your research proposals. If you haven't done so already, you'll take Kean IRB's human subjects protection course and submit to me your course completion certificate. You'll also do a series of in-class and homework exercises that will give you a feel for the various research methods you'll have the option of using for your study. By about week five of the course you'll submit to me your research proposal.

Very Important Point: While this proposal will undoubtely be similar to the proposal you submitted in CJ_3675, it will not be identical to that proposal. CJ_4600 is a different course. You'll need to revise your CJ_3675 proposal to fit the requirements of CJ_4600. We'll go over this more in class. This is just a heads-up.

I typically grade the proposals in about a week, then return them to the students. You'll either be Approved to Begin, Approved-With-Revisions to Begin, or Not Approved. For the non-approved students, you'll have a week to fix the problems and then you'll meet with me again to explain what you did. By about the 7th or 8th week in the semester, everyone should have begun their data gathering.

By about the 10th or 11th week in the semester, the entire class goes to the computer lab to begin data entry and preliminary analyses. In my experience, this is when most students need a lot of hand-holding from the professor. I will get to each and every one of you, and only ask that you remember that there's only one of me and 25 of you in every class. So just be patient. I'll get to you, I promise.

By week 13 or 14, the final papers are due. During the last two classes, students present their findings to their fellow classmates and me. I'll send everyone a template powerpoint presentation to use as a model for their own slides.

One final point, which you'll probably hear me say in class too - everything I'm asking you to do, I've done myself. Proposal writing - check. Surveys and focus groups - check. Content analysis - check. Analyzing existing databases - check. This summer I'm doing both a content analysis and analyzing data from an existing database. I wouldn't ask you to do anything that I myself didn't have a hands-on feel for, if that's any consolation.

In a nutshell, that's it. I promise you'll survive and move on to graduation. And if you have any plans to attend graduate school (hello, Kean MA in CJ program http://www.kean.edu/~keangrad/CHSS/MA_in_Criminal_Justice.html), having done an original research study like what you'll do in CJ_4600 will help your application. If you like doing the kinds of research work we'll do in Seminar, then graduate school might be for you.

Enjoy the rest of your summer, and I'll see you in September.

Best,

Dr. Hassett-Walker

Content Analysis: Next Steps

You're proposing to do a content analysis. Dr. Hassett-Walker has approved (or approved with revisions) your study. Now what?

Here's what you do next (i.e., beginning your study):

(1) Do the search of your selected content. Ex: Searching in Westlaw for past articles in the NY Times and the Washington Post, during the years 2000-2010. Your search terms are "university" and "campus" and "violence" and "victims" (for a study - my hypothetical example - about the effect of violence on college and university campuses on primary and secondary victims).

Note: your search terms will be similar, probably, to some of your code list words.

Suppose 8,547 articles come up. You don't need that many. You need 100, but will randomly select 200 to account for some articles (let's say every other one) being non-relevant or less relevant.

(2) At Randomizer.org, generate a random number list. I just did this, and told Randomizer to give me 1 set of 200 randomly generated numbers, ranging from 1 through 8,547. Here's part of the list it gave me: 49, 2387, 4163, 3955, 4424, 2349, 77, 2422, 3480, 128, 5972, 1579, 3784, 2312, 624, 5602, 876, 2977, 2948, 6856, 2736, 7490, 2117, 7590, 4569, 2844, 2071, 5033, 6005, 2112, 4073, 3580, 7596, 7362, 7066, 1793, 5914, 2815, 7584, 3384, 118...

(3) Next, I find those articles that correspond to the numbers in the random number list. I copy/paste them into a Word or Word Perfect document.

(4) Now I begin reading the articles. Working in Word (rather than on paper), I use the Word artist function to color-code red all words and phrasings related to violence and shootings (e.g., shooting, gun, shots fired, etc.). I color-code green all words and phrasings related to victims (e.g., victim, victims, witness, students standing there watching, etc.) I color-code yellow all words and phrasings related to college or university campus (e.g., campus, college, university, classrooms, buildings, etc.). I color-code blue all words and phrasings related to programs the university or college put into place to help victims.

(5) I set up a database skeleton in SPSS. Before I can enter any data into the database, I must create my variables. These will correspond to my code list. EXAMPLE of variable name (variable #1) and corresponding label: ArticleNum, which newspaper did it comes from (1=NYT, 2=Washington Post). Next variable name: VictimNum, number of times victim or victims mentioned in article. Next variable name: VictimLang, language used to describe victims. Etc.

Note: any variables that involve counting will be numeric variables. Any variables that will have me inputting words will be string variables.

Remember: You set up your SPSS database in variable view.

(6) Once I have my SPSS skeleton set up, I can enter my data (words, language, counts of words) into SPSS. I can either do this once I'm done reading all the articles, or as I go. Remember: you enter your data into your database in data view.

(7) Once you've entered all your data, you run your preliminary and "main" analyses: frequencies, descriptives, and perhaps a correlation analysis. Review your results with Dr. Hassett-Walker. Do you think you are finding support for your research question or hypothesis?

(8) Once you have determined which relationships are significantly related to each other, go back to the color-coded newspaper articles that make up your data. Search for the text coded with the code words that pertain to those statistically significant relationships. That's the text you want to read and perhaps copy/paste into a separate word document. Boil it down into a succinct one to two-paragraph summary/summaries that further explains the statistically significant relationships you found with the quantitative data.

Survey and Focus Group Methodology, Analyses, Results

For the students doing the survey and focus group option, once I've approved (or approved with revisions) your study, you're ready to start.

(1) Print out your consent form on Kean letterhead, which you'll get from me. You and I both sign in the appropriate places. Then you make around 50 copies (two for each student/human subject, one of which they sign and return to you, the other of which they keep).

(2) Make 25+ copies of your survey instrument as well. Your subjects will be filling this out, so it has to be in a form that's ready-to-use for them.

(3) Next step: subject recruitment. You should have already been thinking about this, and/or written it down as part of your method section. Where and when will you find your fellow Kean (NO OCC students!) students? Student Center? Library? Around campus? How will you approach them? If they say yes, you should hand them a consent form to sign. Once they've read, signed, and returned the consent form (keeping a copy for themselves), you'll need to take them to the location where you'll conduct the focus group. Plan and pick your location ahead of time. It should be somewhere you're allowed to be (empty classroom? Empty study room in the library?) that is quiet and has access to outlets, if your tape recorder needs to be plugged in.

(4) Equipment: Also plan this ahead of time. You need tapes that run long enough (1 hour should be good), maybe extention cord, extra batteries, and perhaps an extra tape recorder.

(5) Visualize where you will put the tape recorder, and how your subjects will sit around it. They should sit in a circle, with the tape recorder in the middle.

(6) During the focus group, periodically check that the tape recorder(s) are running, that they haven't timed out.

(7) Immediately after each focus group, spend some time writing down everything you can think about that happened during the focus group. What was the mood? Was everyone equally talkative? Were some students (probably) more talkative than others? What were some of the key points discussed? Write as if you might discover that neither of your tape recordings worked, so you want to be as thorough as possible in writing down what went on and what was discussed.

(8) Once you have all your surveys collected and focus groups conducted, you enter the survey data into a SPSS database that you create. (Email Dr. Hassett-Walker if you need help setting up a skeleton for this.) You'll also spend a few hours typing up everything that's on the tapes. (Play-stop-rewind, play-stop-rewind, play-stop-rewind.... Yes, it's a tedious process.) In the end, you should have a transcript that's perhaps 60-75 pages long. If you ever took a drama class in high school, what you produce will be similar to a script for a play. Note: You don't have to capture every "um" and "ah."

(9) As a reminder, the Krueger book on conducting and analyzing focus groups is on reserve at the OCC library.

(10) Once all your survey data are entered into SPSS and your focus group transcripts are typed up, you are ready to begin analyzing your data and summarizing your findings. You are doing quantitative (of the survey data) and qualitative (of the focus group transcripts) analyses.

(11) The quantitative analyses: this will be the focus of our lab visits in late March. That said, you already know what these are, as you've run them in Methods and Seminar: frequencies, descriptives, correlations and crosstabs with a chi square test, as appropriate. Also refer to p.11 in your course syllabus.

(12) The qualitative analysis: This will basically involve reading the transcript, and determining what group #1 said about question #1, what group #2 said about question #1, what group #3 said about question #1, etc. If it's easier, you can open up a separate Word (or Word Perfect) document and copy/paste text from the original transcript into that new document, under the subheading of (for instance), "All groups' feedback on question #1." So then you have all your text about question #1 in one place; then all your text about question #2 in one place; etc. You want to read through it, summarize it, shorten it so that you have a short, concise 1-2 (or longer) paragraph summary of the key points and themes from the focus group discussions, and a few quotes that "pop", that describe what your subjects felt about the issue that was question #1 (and question #2, and question #3, etc.). Ask yourself how the focus group discussions (your qualitative data) reinforce, condradict, or further clarify your survey findings.

In your final paper, each summary paragraph of the qualitative data will go after each relevant quantitative data table (e.g., of frequencies or correlations), and your paragraph summary of what's in the table.

(13) Example of part of a results section from a paper I wrote:

RESULTS
Fourteen (n=14) Kean University students took the survey and participated in one of several focus groups. Demographically, 79 percent of participants were women, and 21 percent were men. Half the sample (50%) was Caucasian, 14 percent was Black, and 14 percent was Asian. In terms of ethnicity, 21 percent self-identified as Hispanic. Mean age of the sample was 28 years. Socio-economically, nearly 29 percent of the sample self-identified as working class. Thirty-five percent of survey/focus group participants indicated they were middle class, and 35 percent self-identified as upper middle class.

"The guys basically went to an ivy league school”: Class Difference between the Women Performers and the Lacrosse Team Members

Most participants – just over 71 percent – agreed or strongly agreed that the women performers and male lacrosse team members were in different social class groups, as seen in Table 1, below.

Table 1: Women Performers and Lacrosse Team Members were in Different Social Class Groups (n=14)
Agreed or strongly agreed: n=10, 71.4%
Neither agreed nor disagreed: n=2, 14.3%
Disagreed or strongly disagreed: n=2, 14.3%
TOTAL: n=14, 100.0%

[NOTE: THE ABOVE TABLE ISN'T COMING ACROSS WELL IN THE BLOG. IN THE ACTUAL PAPER, IT'S A TABLE IN WORD.]

[HERE’S WHERE MY SUMMARY OF THE FOCUS GROUP FINDINGS COMES IN, INCLUDING SOME SPECIFIC QUOTES]
Some participants felt the women and men were in different class groups because the men “could hire expensive lawyers” whereas one of the dancers, Crystal Mangum, came from a more modest background, being the “daughter of a retired auto-mechanic… that, like, pretty much put her in a family of the working class.” In addition, the fact of the men attending Duke University (“ivy of the South”; and “the reputation of the school… ranked the top ten institutions in the country as far as status, and it’s not cheap”) meant that “these kids have money obviously.”

By contrast, the women worked in a profession (exotic dancing) with low occupational prestige. “The fact that they had to dance. I don’t think that would be a woman’s first choice of occupation.” Another participant explained, “dancers…are automatically associated with being strippers or hookers, or being paid for…you are automatically labeled or looked down upon.” Another participant felt that the men “would have disrespected them [the women] anyway because of their job and double disrespected them because of their ethnicity.”

Another participant said that the women likely danced because they had to in order “to pay bills, as opposed to lacrosse team in Duke University. Most likely, they had their parents pay for their education so I would think they’re in different social classes.” Another commented on the fact that the lacrosse team was able to hire the women (“it’s like a lot of money, like $500 right off the bat”), suggesting that the employer-employee relationship indicated a class difference between the men (employer) and the women (employee).

THE IDEA IS TO USE THE DISCUSSION FROM THE FOCUS TO FURTHER EXPLAIN OR CONTRADICT WHAT THE SURVEY FINDINGS (PRESENTED IN TABLE FORMAT) TELL YOU. SURVEYS TELL YOU COUNTS AND PERCENTAGES OF RESPONSES, BUT THEY DON’T REALLY GET AT THE “WHY” AND “HOW” AND “WHY DO YOU THINK THAT.” THAT’S WHERE THE FOCUS GROUP RESULTS COME IN.