Class 5

Please bring your Research Methods paper to the front table and make sure it has your

name on it.

Class Agenda

Announcements Dale Carnegie SpeechesExecutive Summary MistakesFindings Advice Coding Open Ended Responses

To Me, Citizenship…

Health Navigator

Dale Carnegie Speeches

• Michael • Colleen • Victoria • Jenna • Leah • Monika

Format of Ex. Summary

Use Times New Roman- Size 12

WATCH YOUR SPACING

Finding numbers should be left justified

No demographics in findings unless you are profiling clients

No decimals in percentages EVIL 24.6%

Using % When Reporting Sample Size

Describe sample as percent of target population in Ex. Summary E.g., With a target population of 100, 10 surveys (10%) were collected.

COPLIN WILL BE FURIOUS IF YOU DON’T DO THIS

WritingLearn how to use commas and avoid ; or : as conjunctions

Data were, not was

No repetition

Say “mail” survey; not “mailing survey” or “mailed survey”

Avoid too much detail on methods in the Exec Summary

Put target population, sampling frame (if there is one) and sample in one sentence

Make sure reader knows how you got the data and include date(s) if records

Don’t get heavy into representativeness. Say either:

• “The sample is likely to represent the target population because….”

• “The sample may not represent the target population because…” (of its small size or differences in demographics between the sample and target population)

More Dont’s Put demographics in Ex. Summary Findings

Confuse absolute numbers with rates

Incorrectly using the word “random”

Use the plural to refer to your agency like “they are trying to improve their program” Write either “the Agency staff is” or “Members of the agency staff are”

USE UTILIZE

WORDS YOU NEVER USE In this Report

Assess and evaluate to describe your study. You are reporting not making judgments.

Effective and efficient. You can’t possibly know that from your data.

Don’t say “respondents are unhappy.” Say “respondents said they were unhappy” You only know what they said.

If your executive summary says “See Me” you must make an appointment hopefully with your TA with Coplin BEFORE class next week unless you already have today.

Findings and Analysis

Some general principles in conducting your data analysis and developing graphs for your findings.

Decide Interval, Ordinal, Nominal

Interval—Variables continuous numbers like weight Ordinal—Variables have categories that are ordered in some way Nominal—Variables are unordered categories

Interval

Averages Trend linesCan be categorized for bar graphs

Nominal Categories represent in bars must be ranked by percentages Example: open ended responses or “check all that apply” questions

The most frequently mentioned characteristic of the client was “friendly” (81%).

Ordinal Bar graphs where the bars must be ranked according to the order of the categories. E.g., very dissatisfied, satisfied, neutral, satisfied, very dissatisfied

60% of respondents said they were “very dissatisfied” or “dissatisfied” with Enable’s services.

25%

35% 35%

5%

0%5%

10%15%20%25%30%35%40%

Very Dissatisfied Dissatisfied Satisfied Very Satisfied

Per

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Level of Satisfaction

Respondents' Satisfaction with Fire Protectionn=20

Step 2: Univariate or Bivariate Analysis?

“Uni” means oneLook at each variable separately--range, mean and Standard Deviation if it is a numberFrequencies if it is nominalMost of your findings will be univariateGrouping interval data to make it ordinal –creating ranges

Univariate Analysis for Nominal Variables

Rank frequencies in percentages from high to low Ex. demographic, Female 51% Male 49%Ex. Number of People in Programs A-C

Program C—43%Program A—38%Program B-19%

What about Bivariate Analysis?

Bi means twoInvolves looking at 2 variables

Example: Does gender relate to whether respondents like or dislike the program?

3 ways to display this information

Bivariate Analysis Example 1BAD

50%

5%

0%

10%

20%

30%

40%

50%

60%

Like Dislike

Per

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Feelings About Program

Male Respondents' Feelings about the Programn=100

15%

30%

0%

10%

20%

30%

40%

50%

60%

Like Dislike

Per

cen

t of

Res

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Feelings About Program

Female Respondents' Feelings about the Programn=100

Example 2:Two Color Graph- BAD

Bivariate Analysis Example 3GOOD

Contingency Tables

Method to see if one variable is correlated with another.

Will be discussed more in next classes

Coding Open-Ended Responses

List actual responsesAggregate into categoriesGraph categoriesInclude category name with actual responses listed below in appendix (sample on next slide)

How would you improve PAF 315?

Raw Responses:Change final paperEliminate disorderly studentsScreen clients betterRequire clients to have surveyEliminate smaller papersChange final paperMake Clients accountableEliminate final paperDon’t do faculty contactChange professor

Aggregated Responses:Alter Assignments 5 Change final paper (3)Eliminate smaller papersDon’t do faculty contactImprove Clients 3 Screen Clients betterRequire clients to have surveyMake clients accountableOther 2Eliminate disorderly studentsChange professor

How would you improve PAF 315?Aggregated Responses:Alter Assignments 5 Change final paper (3)Eliminate smaller papersDon’t do faculty contactImprove Clients 3 Screen Clients betterRequire clients to have surveyMake clients accountableOther 2Eliminate disorderly studentsChange professor

1. The most frequent response for how to improve PAF315 was “Alter Assignments” at 50%.

Source: Study done by XYZ agency, 2004

Comment: Of the 10 respondents who gave specific ways to improve PAF 315, 3 respondents (17%) suggested to “change the final paper.” See Appendix II for complete list of responses.

Coding Open-Ended Questions

Complete worksheet

3-5 categories

We’ll discuss as a class

Categories for Open-Ended Exercise

Salary and benefitsWorking conditions – facility SupervisorsSafety and healthOffice complaints

Appendix III- Open Ended Responses

Reminders

Due next class 2/18:Formatted Report Shell (we will show you in training)

Due in 3 weeks 3/4:Rough Draft

Dale Carnegie Next Week 2/18• Michael • Colleen • Victoria • Jenna • Leah • Monika

Supervisor Meeting

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