Download RESEARCH LAB II (S3) Salem State College School of Social Work

Research for Social Workers
Salem State University
School of Social Work
Class 10
Jeff Driskell, MSW, PhD
Today’s Class
• Announcements/Check-in
• Lecture
▫ Data Analysis
 Frequencies
 Descriptive Statistics
 Measures of central tendency
• Work time
Reflection- Class 10
• Article Reflection
▫ What are the indicators that lead you to believe
your article is qualitative in nature (other than it
saying so)?
▫ What type of method selected (i.e. grounded
theory)
• Hypothetically the study you are proposing is
qualitative in nature. Identify three types of rigor
you would employ to increase trustworthiness.

Statistics and Interpretation
Statistics
• Holistic Approach▫ collection, analysis, interpretation/ explanation, and
presentation of data.
• It provides tools for▫ description, prediction, and relationship identification
• Levels- What are the levels at which analysis are
conducted?
▫ Univariate- Statistics that describe one variable at a time
▫ Bivariate- Statistics that looks at the relationship between two
variables.
▫ Multivariate- Statistics that looks at the relationship between
multiple variables
Ways to Organize and Present Data
1.Tables
▫
▫
Descriptive tables
Frequency tables
2.Graphs
▫
▫
Bar
Histogram
3.Narrative
4.Matrix
▫
Correlation
Statistical Analysis- What you need to
know
I. Purpose of test
Match question to test

II. Logistics for test
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
○
○
Structure of variable needed for test
Continuous
Nominal
Number of variables needed for test
III. Interpret test findings

Basic knowledge of the “squigglies” in reporting
statistical results
Review: Variable structure
• Provide an example of a continuous level
variable
• Provide an example of a discrete level variable
Types and Categories of
Statistical Tests
4 basic categories of statistical tests
Description
• Mean, standard deviation
• Median, Mode
• Percentage, frequency
Correlation
• Pearson’s correlation
Comparison
Prediction
•
•
•
•
Student’s t tests
Chi-square tests
ANOVA
Odds ratios
• OLS regression
• Logistic regression
Statistical Tests: Implications of
Normal Distributions
• Two categories of statistical tests
▫ 1. Parametric
 Used for normally distributed data
 Example- T-test, ANOVA
 Correlation Coefficient
▫ 2. Non-parametric
 Used for non-normally distributed data





Mann-Whitney
Wilcoxon’s matched tests
Chi Square
Kendall
Spearman R
If You Want to Describe or
Summarize Variables…
Univariate & Descriptive
• Univariate - describe individual variables
• Descriptive – describe, summarize data
•
•
•
•
•
Frequency
Range
Percentage
Central tendency (simple mean, median mode)
Standard deviation
Frequencies
A Frequency (f) is a count of the number of
cases or characteristics of selected cases, i.e. the
number of treatment sessions attended.
Frequency Distributions
• Two ways to display Frequency Distributions
1. Frequency tables
2. Histograms/Bar charts/Pie Graphs
Where do the Numbers Come
From? Frequency Output in SPSS
Example- Frequency Table
Table 1
Frequency Distribution: Number of Children Reported by Parenting Class Participants
Number of Children
Frequency (f)
1
11
2
1
3
4
4
5
5
0
6
2
Total= 35
Example- Bar Graph
Histogram
Descriptive
Descriptive Statistics
▫ Statistical procedures used to summarise,
organize, and simplify data.
 Raw data is made more manageable
 Raw data is presented in a logical form
 Patterns can be seen from organized data




Frequency tables
Graphical techniques
Measures of Central Tendency
Measures of Spread (variability)
Measures of Central Tendency
▫ A way of summarising the data using a single
value that is in some way is representative of the
entire data set. Three options…
1. Mode
 Most frequent value occurring in your data
(frequency)
 Unaffected by extreme scores (outliers)
 Not useful when there are several values that occur
equally often in a set. However can be more than one
mode
 Can be measured on any level
Measures of Central Tendency
2. Median
 The values that falls exactly in the midpoint of a
ranked distribution (50th percentile)
 Unaffected by extreme scores (outliers)
3. Mean (Arithmetic average)
 Average score
 Preferred measure; Most commonly reported
measure
 Only for continuous variables (ratio, interval)
 Easily distorted by extreme values (outliers)
Standard deviation
• Most commonly used measure of dispersion
around a mean
▫ how “spread out” are the values?
• Always reported with the mean – otherwise
considered to be biased
• Can’t be done with nominal variables
Table 1: Demographics of Elders with MR/SA
Sociobehavioral
model
Predisposing
Characteristics
Enabling
resources
Need factors
***p<.001 *p<.05
Variable
MR/SA
(N=350)
NoMR/SA
(N=48,014)
Test
Gender (male)
238 (68%)
25,064 (52%)
OR=1.9***
Mean age (SD)
70 (5)
73 (7)
t=4.5*
Race (white)
260 (74%)
28,741 (59%)
OR=1.9***
(SSI/SSDI)
199 (57%)
29,131 (61%)
NS
Dually eligible
303 (87%)
43,226 (90%)
OR=0.7*
FFS coverage
262 (75%)
34,283 (71%)
NS
Low state SA
coverage
141 (40%)
16,899 (35%)
OR= OR= 1.2*
Urban location
213 (61%)
30,027 (63%)
NS
SMI diagnosis
151 (43%)
7,540 (16%)
OR= 4.1***
Long-term SA
diagnosis
19 (5%)
5,549 (12%)
OR= 0.4***
Bimodal Example
Diagnostic Category
1.
2.
3.
4.
5.
Anxiety disorders
Eating disorders
Mood disorders
Personality disorders
Psychotic disorders
Number of Clients
(Frequency)
1. 8
2. 4
3. 8
4. 3
5. 5
Measures of Dispersion
Dispersion
Definition- Measures the dispersion of
responses of a given variable. i.e. Age
Types
1. Range
2. Standard deviation
The Range
• Easiest measure to calculate and simplest to
understand
• Weakest measure
• Influenced by outliers (extreme measures) in
your data set
• Example- Age range of adolescent girls in
outpatient treatment for Oxycontin at Victory
Programs. Range= 13-18 years of age.
Standard Deviation (SD)
• Most commonly used measure of dispersion around a
mean
▫ how “spread out” are the values.
▫ Tells us how far the average scores varies from the
mean
• Measured at the interval or ratio level and sometimes the
ordinal level
• The smaller the SD, the more the scores cluster around
the mean.
• The larger the SD, the more the scores are spread or
dispersed away from the mean. Never a negative value.
• Goal+ small SD as it will be a more representative of the
mean (average) of the data
Demographics Table
Text Supporting Previous Table
Buzi et al. (2007) Reading
• What is the study rational?
• What is the mean age of the participants?
Range?
• What scale was used to measure depression?
What is the reliability of this scale?
• What is the frequency of individuals who
reported having at least one drink of alcohol in
the past 30 days?
Narrative Example
Qualitative Example- Demographics
Choosing Measures of Central
Tendency- Variable Types
Measures
Mean
Best Uses
4 Interval or ratio data
Median
4 Ordinal, interval, or ratio data
Mode
4 Nominal, ordinal, interval, or ratio
data