Data Analysis and Presentation Social Work 176 Data Analysis and Presentation

This course includes: Lectures on Qualitative Data and Statistics Exercises for Each Class Two exams (midterm and final) Four Assignments Computer Assisted Instruction Class lectures will be in powerpoint. You can view the powerpoint lecture on your computer terminal.

All course material is posted on the following web site: http://zimmer.csufresno.edu/~donnah

The website contains Course syllabus Course outline Assignments Powerpoint lecturers with class exercises A dataset to use with SPSS A “code” book with information about how variables were measured. An SPSS handout.

Important information!!! Total points for the class total 600. A 90% is an A. If you receive 540 points before the final exam, you may be excused from the exam. Please note that all Assignments contain extra credit!

The assignments require that you: Analyze data Write up a description of your analysis. Three of the assignments require that you use SPSS, a statistical software package, to calculate statistics. You will be given class time to “run” your data. For Assignment #1, you will collect your own data and analyze it.

You must bring to class: A floppy disk to save your work. A copy card, available from the library, to print out your work. A good attitude!

The Assignments Are: An analysis of data from three interviews that you will conduct. Analysis of descriptive data using SPSS. Analysis that compares data about different groups of people (cross-tabulation and chi-square). Analysis of inferential statistics.

The Three Statistics Assignments require that you: Use a data set (that is posted on the web site) to run data to answer several research questions. Create a computer print out or a disk copy of the statistics you have run to turn in. Write up a written description of what you have found. Written descriptions should be no more than one to two pages.

The exams will require: You must come to class, read the book, and read the powerpoint lectures to pass the exams. The exams will be multiple choice, short answer, and some simple calculations (for example averages and percentages). Both exams will be cumulative, testing you on all the content covered in class up until that point.

Class Exercises Will follow all lectures. Usually lectures will be on Tuesday and exercises will be on Thursday. Will be done in groups. Will contain content on both qualitative and quantitative methods. Will require that you apply knowledge from the book and the lectures to the analysis of data.

Class Rules No food or drink in the lab. Attendance will be taken. Contact the instructor before the class to request an excused absence. Since it is difficult to see and hear in the class, please do not talk during lectures except to ask or answer questions. Do not use the computer terminal to play solitaire or work on other assignments!!!

Class Content Covers Several Types of Data Analysis Qualitative (data collected through observation, open-ended interview or content analysis). Quantitative: Descriptive Statistics (frequencies, means, standard deviations, and cross-tabs) Inferential Statistics (t-test, ANOVA, correlation, and regression) Nonparametric Statistics (Chi-square)

Other things we need to know to analyze data Concepts Variables Operational Definitions Independent and Dependent Variables Difference between qualitative and quantitative methods

Differences between qualitative and quantitative research Involves unstructured interviews, observation, and content analysis. Subjective Inductive Little structure Little manipulation of subjects Takes a great deal of time to conduct Little social distance between researcher and subject Involves experiments, surveys, testing, and structured content analysis, interviews, and observation. Objective Deductive High degree of structure Some manipulation of subjects May take little time to conduct Much social distance between researcher and subject

Concepts can be: One dimensional and have only one value. (For example if you only interview women, gender = women). Some concepts have multiple subparts or categories. (Gender = Male or Female).

In qualitative research: We use simple concepts. We describe the concept that will be measured.

In quantitative research: We construct operational definitions that include: 1) A detailed definition of the concept 2) Information about the scope of the concept measured. 3) Detailed information about how the concept will be measured. Standardized, structured methods for collecting the data are described. The concepts will contain several different values or categories (variables). We also derive our concepts from previous theories. We examine how previous researchers have defined the concept. One approach to research, meta analysis, examines how operational definitions vary from study to study and how these definitions influence the findings.

Examples of concepts/variables: Qualitative: Perceptions of domestic violence; interactions between clients and workers in a public agency; Hmong beliefs about birthing practices. Quantitative: Depression; Self-Efficacy; Support for Candidate; Drop-out Rates.

Concepts are: Used to express an abstract idea. Are often related to other concepts. Contain a definition of the concept. Contain some information about the scope of the concept. For example, we can define social work students in a variety of ways – all MSW students, all students in this class, etc.) Can be found through experience, observation, or from previous theories or empirical research. Dictionary definitions can also be used to define concepts.

As measured using Beck’s Depression Inventory To create an operational definition, we need to both define the concept and state how we will measure it: Depression: A state of excessive sadness or hopelessness, often with physical symptoms (Oxford American Dictionary, 1980). As measured using Beck’s Depression Inventory You should also include the target population (scope) in the operational definition. For example, depression among adolescent girls, age 13-18.

Independent Variables Produce a change in a second variable. Are introduced before the second variable Require that an actual link between the two variables can be established. In social work, independent variables are usually interventions that are to be used to change individuals, families, communities, or organizations. In some cases independent variables can be an attribute of an individual that determines a second attribute. For example, there is research evidence that women make less money than men. Variables are – independent (gender) and dependent (income).

Dependent Variables are: Things or attributes about a person that are to be changed. Dependent variables are introduced or come after the independent variable. An actual link between the two variables can be established.

Hypotheses: Specify the relationship among two or more variables. Are stated in situations when we want to test whether there actually is a relationship between two variables. Are stated when we want to determine if there is a reason that it only appears that there is a relationship between two variables (spurious relationship), but one does not really exist. Most often specify whether there is a positive or negative relationship between the two variables (does the value of the second variable increase when the value of the first increases or does the value of the second go down when the value of the first increases). Should only be used with inferential or nonparametric statistics.

Research Questions: Should be used for qualitative or descriptive research. When there are no independent or dependent variables. (Qualitative or Descriptive Research) When we only want to find out if some type of relationship may exist between two variables, but do not want to check to see the strength of the relationship.

Other important concepts for data analysis are population and sample Population – the group of people studied. Sample – a smaller subset or group of the universe of people studied. Sampling methods can include either probability or nonprobability samples. Descriptive and qualitative research often use nonprobability approaches. To use inferential statistics (testing hypotheses), you ideally must have a random sample!

Week 1: Class Exercise #1 With a group of at least three students: Write a research question about a social work issue that you want to find out more about. Try to determine if you will need to use qualitative approaches (observations; perceptions of the people studied) or quantitative approaches (data based on counting or measuring) to answer this question.

Week 1: Exercise 2 Are the following statements research questions or hypotheses? How do Lao parents communicate with their children? There is a positive association between gender and self-esteem. Multisystems social work practice using an empowerment approach increases a client’s feelings of personal self-efficacy and control. How do people in low-income neighborhoods perceive each of the Presidential candidates?

Week 1: Exercise 3 What are the independent and dependent variables in the two hypotheses from the previous slide? There is a positive association between gender and self-esteem. Multisystems social work practice using an empowerment approach increases a client’s feelings of personal self-efficacy and control.

Next week we will: Talk about research ethics. Talk about using research for social justice and empowerment. Talk about cultural competency in research. Talk about types of data and levels of measurement.