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Class Notes
(839,296)

Canada
(511,254)

University of Toronto Mississauga
(24,116)

Sociology
(4,081)

SOC222H5
(93)

John Kervin
(32)

Lecture

Department

Sociology

Course Code

SOC222H5

Professor

John Kervin

Description

SOC 222 -- MEASURING the SOCIAL WORLD
TABLES -- Session #2
WHERE WE ARE
Ratio is quantitative and all other categories are category
**Today variables will either be nominal or ordinal
• Will have to variables, like male or female
Today’s Objectives: Know…
1. The difference between causation and correlation
2. Three criteria for causation
3. Importance of the three types of bivariate relationships
4. The two kinds of statistics and two key questions in statistics
5. Difference between a percentage and a proportion
6. How to produce a bar chart in SPSS
7. Measures of central tendency for category variables
8. How to produce a crosstabulation in SPSS
9. How to percentage tables
10. How to produce a bivariate clustered bar chart
Terms to Know
independent variable
dependent variable
covariation
descriptive statistics
inferential statistics
representative sample
frequency distribution
central tendency
mode
median
crosstab
effect size
BIVARIATE RELATIONSHIPS
xy- how we indicate this
x causes y
Dependent and Independent Variables
Dependent vs. independent variable- depends, wearing them is effect of aging Causation and Correlation
If we find that there’s correlation between poverty and internet use can we determine internet
use causes poverty? No!
Criteria: to say that x causes y
1. Time Order: X must come before Y in time, that’s why sex is a determinant, if males
make more money, you would say earnings determine sex
2.Covariation: X changes, Y changes what ever happens is systematic. One variable varies
with another variable, what stats focuses on
3. Non-spurious: does X vary systematically with Y,
Three Types of Bivariate Relationships
**Category and ratio variables
DV
IV: Cat Rat
Cat Cat Cat Cat Rat
Rat Rat Cat Rat Rat
• There are 4 possible types
• Catrat, important but not for us, basis of experimental designs
• Ratrat- that’s us, what we will look at, regression analysis- procedure that
dominates sociology today
•
Importance of Each Type:
The Two Key Questions
Two things can get in the way of showing there’s co-variation
Descriptive : is there a relationship? How strong is it? And what direction does it take?
How strong is relationship between x and y
Inferential : if we base conclusion about co-variation on sample and then want to draw on
sample…..sample mean we don’t get info from every possible source.
always possibility that the sample is bad and doesn’t capture the whole population.
Only applies when we have a sample, and asks how accurate it is if we base it on our sample representative sample
CATEGORY VARIABLES
Frequency Distributions
Not so usefull for ratio variables, too many pages and numbers
• Tell us what categories there are, what percentage of people are in each category
• Percentage is out of 100, counts of things are sometimes hard to understand
Percentage and Proportion
• Proportions are same thing but instead you just take number and divide it by 100
SPSS Frequency Distributions
• Give us counts and percentages
Department
Cumulative
Frequency Percent Valid Percent Percent
Valid Chem Eng 29 10.2 10.2 10.2
Elec and Comp Eng 47 16.5 16.5 26.8
East Asian Studies 39 13.7 13.7 40.5
English 20 7.0 7.0 47.5
Microbiology 63 22.2 22.2 69.7
Botany 19 6.7 6.7 76.4
Geography 11 3.9 3.9 80.3
Economics 38 13.4 13.4 93.7
Sociology 18 6.3 6.3 100.0
Total 284 100.0 100.0
The table shows:
• Bar Charts
SPSS Bar Charts
• Best graph is a bar chart for category variables
•
SPSS Bar Charts
Open data set
Click on “Graphs” on menu bar
Choose “Chart Builder” from dropdown menu
This opens the “Chart Builder” procedure box
• Top left: list of your variables
• Next to it: a white working area
• Bottom:
• A “Choose from” box. AKA “the gallery”
• On top of this box: four selection buttons
• Underneath: the five action buttons
Steps:
1. Decide which general type of graphic you want (left side of “Choose from” box)
2. Within that general type, pick the specific type (icons – will show name of type)
• Simple bar chart is on the left
3. Drag icon up to white working area
• This shows a sample of what you’ll get, with some spaces to fill in to complete
your chart
4. Drag your category variable into the X-axis area
• X-axis will show variable label
• Vertical Y-axis will show “Count”
5. Click “OK”
• The bar chart will show up in your output window. (Name of procedure will be
“GGraph”) If you want to see percentages instead of counts:
• Open the “Element Properties” box (if it’s not already open)
• Edit Properties: Bar 1
• In “Statistics” area, under “Statistic”, pick “Percentage” on drop-down menu
• Ignore the question mark (since you’re percentaging on the total)
• Click “Apply”, then “Close”
• Result: exactly the same appearance, but percentages i/o counts Central Tendency: Category Variables
Nominal Variables
• Mode: the category with the highest frequency
Department
Cumulative
Frequency Percent Valid Percent Percent
Valid Chem Eng 29 10.2 10.2 10.2
Elec and Comp Eng 47 16.5 16.5 26.8
East Asian Studies 39 13.7 13.7 40.5
English 20 7.0 7.0 47.5
Microbiology 63 22.2 22.2 69.7
Botany 19 6.7 6.7 76.4
Geography 11 3.9 3.9 80.3
Economics 38 13.4 13.4 93.7
Sociology 18 6.3 6.3 100.0
Total 284 100.0 100.0
Ordinal Variables
Median: The category containing the case in the middle of the frequency distribution Right major = good job
Cumulative

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