Download Continuous variables

ScWk 298
Quantitative Review Session
Types of Variables
Categorical variables:
Continuous variables:
Nominal: categories with no
ranking (e.g. gender,
race/ethnicity, place of
birth, etc.)
Ordinal: categories with a
ranking (e.g. educational
level, income categories,
Likert scales (strongly
agree, agree, disagree,
strongly disagree) etc.)
A zero point and equal
distance between values
(e.g. age, height, weight, #
of hours studying a day,
etc.).
What kind of variable is it?
The number of visits to a homeless
shelter ________
 How satisfied are you on a scale of 1
(Very satisfied) to 5 (Very dissatisfied)?
_______
 Have you ever had training in Cognitive
Behavioral Therapy? (Yes/No)? ____
 Student’s GPA _____

Descriptive Statistics:
Categorical Variables
Frequencies and percentages are used
with categorical variables
 Frequency: a count
 Percentage: a proportion of the total

Child.Gender
Valid
Frequency
F
1955
48.8
50.6
50.6
M
1909
47.6
49.4
100.0
Total
3864
96.4
100.0
146
3.6
4010
100.0
Missing X
Total
Percent
Cumulative
Valid Percent Percent
What’s the difference between Percent, Valid
Percent and Cumulative Percent?
Which one should you report?
Descriptive Statistics:
Continuous Variables
Means, medians, standard deviations, and
ranges are used with continuous variables
 Mean: average (add all values and divide by total
number of values)
 Median: when all of the values are put in order
from lowest to highest, the median is the middle
number
*Use median instead of mean when there are
outliers (extreme high or low values)

Descriptive Statistics:
Continuous Variables
Standard deviation: A number that reflects
how much variation there is from the
average value in the dataset. A large SD
indicates a lot of values that are different
from the mean. A small SD means there are
not a lot of values that are different from the
mean.
 Range: The highest value in the dataset
minus the smallest value in the dataset

Descriptive Statistics
N
child age in
months
4010
Valid N (listwise)
4010
Maximu
m
Minimum
.00
Mean
215.00 88.1387
Std.
Deviation
58.30834
Testing Hypotheses
Bivariate statistics test the strength of the
relationship between TWO variables.
 Chi-Square test examines the relationship
between a categorical independent
variable and a categorical dependent
variable

Chi-Square Example
Research Scenario
 Quasi-experimental group research design
examining employment outcomes among
participants in a vocational training program
compared to those on a waiting list
(comparison group).


Independent Variable: Vocational Training
Program vs. waiting list

Dependent Variable: Employment outcomes
Chi-Square SPSS Results
Program.Participation * Employment Crosstabulation
Program.Participation
Intervention Group
Comparison Group
Total
Count
% within Program.
Participation
Count
% within Program.
Participation
Count
% within Program.
Participation
Employment
None
Part-Time Full-Time
5
7
18
Total
30
16.7%
23.3%
60.0%
100.0%
16
7
6
29
55.2%
24.1%
20.7%
100.0%
21
14
24
59
35.6%
23.7%
40.7%
100.0%
Chi-Square Te sts
Pearson Chi-S quare
Lik elihood Rati o
Linear-by-Linear
As soc iation
N of V alid Cases
Value
11.748 a
12.321
11.548
2
2
As ymp. Si g.
(2-sided)
.003
.002
1
.001
df
59
a. 0 c ells (.0% ) have expected count less than 5. The
mi nimum expected count is 6.88.
This is APA format for reporting
Chi-Square results:
X2 = (2, N = 59) = 11.748 , p =
.003
Dependent Samples T Test

Used with a categorical independent
variable and a continuous dependent
variable

Compares Pre-test data to Post-test data
Dependent Samples T-test: Pre-test
and Post-tests

Research Scenario

Quasi-experimental pre-test post-test design
examining changes in client work skills after
participation in a vocational training program

Independent Variable is the vocational training
program (pre-test vs. post-test)

Dependent Variable is a score on an assessment
of work skills
Dependent T-test SPSS Results
Paired Samples Statistics
Mean
Pair
1
Pre-Test Work
Skills Score
Post-Test Work
Skills Score
N
Std. Deviation
Std. Error
Mean
12.7250
40
4.65192
.73553
17.5750
40
6.53546
1.03335
This is APA format for
reporting Dependent
T-test results:
t(39) = - 7.462, p <
.001
Pa ired Sa mples Test
Paired Differences
Mean
Pair
1
Pre-Test Work Skills
Score - Post-Test
-4.85000
Work Skills Score
Std. Deviation
Std. Error
Mean
4.11096
.65000
95% Confidence
Interval of the
Difference
Lower
Upper
-6.16475
-3.53525
t
-7.462
df
Sig. (2-tailed)
39
.000
Independent Samples T Test

Used with a categorical independent
variable and a continuous dependent
variable

Compares data between 2 different groups
Independent Samples T-test

Research Scenario

Quasi-experimental group research design
examining differences in the number of
emergency psychiatric hospitalizations
experienced by mental health clients who are
either in 1) individualized medication support
program versus, 2) a group medication support
program.

Independent Variable is the type of medication
support program (individualized vs. group)

Dependent variable is the number of emergency
psychiatric hospitalizations
Independent Samples T-test SPSS
Results
This is APA
Group Statistics
Number of Emergency
Psychiatric
Hospitalizations
Type of Medication
Support: Group or Ind.
Group Medication Support
Individualized Medication
Support
N
19
19
Std. Error
Mean Std. Deviation
Mean
10.8947
3.51022
.80530
8.1579
3.74556
.85929
format
for reporting
Independent Ttest Results
t(36) = 2.324, p =
.026
Independent Samples Test
Levene's Test for
Equality of Variances
F
Number of Emergency
Psychiatric
Hospitalizations
Equal variances
assumed
Equal variances
not assumed
.019
Sig.
.891
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
2.324
36
.026
2.73684
1.17766
.34843
5.12525
2.324
35.849
.026
2.73684
1.17766
.34808
5.12560
Correlation
Used with a continuous independent
variable and a continuous dependent
variable
 Tests the strength of the association
between the 2 variables

Correlation

Research Scenario

A cross-sectional survey study is examining the
possible association between employee stress
levels and the number of clients they have on
their caseload.

Independent variable is number of clients

Dependent variable is score on a stress survey
Correlation SPSS Results
Corre lations
Number of clients on
caseload
Pears on Correlation
Sig. (2-tailed)
N
Employee stress level Pears on Correlation
Sig. (2-tailed)
N
Number of
clients on
caseload
1
Employee
stress level
.821**
.000
40
40
.821**
1
.000
40
40
**. Correlation is significant at the 0.01 level (2-tailed).
This is APA format for reporting
correlation results
r (40) = .821, p < .001
Other tests


ANOVA: One categorical independent variable
(with 3 or more categories) and one continuous
dependent variable
Multivariate statistics allow you to determine
the impact of an independent variable on a
dependent variable while factoring out the
influence of potentially confounding (i.e.
extraneous) variables. Logistic regression is for a
categorical dependent variable and multiple linear
regression is for a continuous dependent variable
SPSS Resources
Research Sequence website has selfguided SPSS labs with answer keys:
http://www.sjsu.edu/socialwork/courses/Res
earch/
 UCLA SPSS website (LOTS of examples
with detailed instructions):
http://www.ats.ucla.edu/stat/spss/
