Standard Deviations and Standardize Scores
Today
Introduction to standardized scores
o How do you compare apples and oranges?
Review of standard deviation & normal curve
Standard proportions under the normal curve
o Standardized scores
o Zscores
o Cal
Test Review #1
Week 2: Purpose of Social Research
Steps of the Scientific Method
Induction vs. Deduction
o Induction: observation pattern tentative hypothesis theory
o Deduction: theory hypothesis observation confirmation
Additional concepts and ideas
o
PART C
1. Standardized scores
Descriptive Statistics
N
What is the participant's
Minimum
1167
age?
Valid N (listwise)
Maximum
18
Mean
93
Std. Deviation
49.37
15.874
1167
2.
Statistics
What is the
participant's
Valid
the participant's
age?
N
Zscore: What i
Page 1 of 3
SOC 3H06 4/07/16
Quick Review
Two types of measures of association. Where on variable is nominal for those
measures of correlation measures are always between 01. Closer to 0 shows weaker
relationship. If we have both ordinal or interval, th
Page 1 of 3
SOC 3H06 27/06/16
Cross tabulation and ChiSquare
used to examine relationships between non interval level variables (i.e gender and
level of education)
Relatively few categories for each variable
Always compare relative column percentages
Page 1 of 2
SOC 3H06 29/06/16
Measures of Association/Correlation
if a relationship exists between x and y we ask: how strong or weak is it?
i.e place of residence is related to attitudes on abortion, but by how much?
Measures of association/correlatio
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SOC 3H06 1/06/16
Variability and probability
Coefficient of VariationCV
if variables are measured on different scales of the st.dev. cant be used to
compare variabilityi.e income and education. measured in different terms, i.e
amount and y
Page 1 of 2
SOC 3H06 6/06/16
Sampling and the sampling distribution
Rarely are we able to gather information about the entire population; exceptioncensus
So we need methods to gather a sample
Two types of sampling methods:
Non random (nonprobability)
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SOC 3H06 13/06/16
Terminology
Population distributiondistribution for an entire population of values. I.e every country
in the world.
mu=population mean
Population standard deviation
Sample distributiondistribution of the sample from the
Page 1 of 2
SOC 3H06 18/07/16
Example: Wealth and civil liberties
Y=2.58 + 0.003X
t=1.99
sig =0.08
Note the magnitude of the slope does not indicate strength of association
Pearsons r = 0.58
R2 = 0.33
Slope is not measure of correlation or associa
Page 1 of 4
SOC 3H06 15/06/16
1. Sample sample measured twice
i.e reading comprehension before and after breakfast program introduced
Use the T values
2. Difference of proportions
I.e difference in percentage of students passing test, in schools with a
Page 1 of 2
SOC 3H06 25/05/16
Lecture 7
Measures of Variability/Dispersion
answers question of what is atypical
i.e marks distribution in 2 sections of SOC 1A06, with the same average.
The second section has the exact same average, however there is a l
Page 1 of 2
SOC 3H06 11/05/16
Lecture 4
once data is collected:
describe the datawhat is typical, atypical
Test hypothesesis x related to y
Frequency distribution/table is the 1st tool used to summarize/describe a
variable.
A table of frequency of
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SOC 3H06 20/06/16
We do not need to know these formulas for the test.
f test, more than two groups.
The between groups variance is being compared to the ingroups. Higher it is, more
likely to fall in the rejection region.
F ration
F=MS bet
Page 1 of 4
SOC 3H06 4/05/16
The Purpose of Social Research
Age related to crime
If the age profile changes and relatively less younger people over time does this have
an impact on crime over time? You can do this by comparing break and enter crimes
to
page 1 of 4
SOC 3H06 9/05/16
Chapter 1 Continued
Wheel of science starts with theory and ends with theory.
Example of wheel of science
Topic: Immigration and support for social welfare policies
Theory: Class based solidarity is required for popular supp
SPSS ASSIGNMENT 1
SOCIOLOGY 3H06
DR. YOUNG
DECEMBER 5TH, 2016
DATASET ACTIVATE DataSet1.
WEIGHT OFF.
FREQUENCIES VARIABLES=sex1
/ORDER=ANALYSIS.
Part A
Statistics
Respondent Gender
N
Valid
Missing
1211
0
Frequencies
Respondent Gender
Frequency
Valid
Male
Page 1 of 3
SOC 3H06 16/05/16
Organizing Data Lecture 5
Percentiles
measure of how scores ranks relative to other scores, in an ordinal or interval
distribution.
So is a life expectancy of 75.6 years good or bad?
Country with this value has a percentil
Page 1 of 4
SOC 3H06 13/07/16
Experiments
experiments involve doing 2 things:
Taking action (i.e showing a film)
Observing consequences of that action (i.e does opinion or behavior change?)
Not
used as often as other data collection methods:
Many of t
NORMAL CURVE AND REVIEW
Review of Probability
Predict events based on some mathematical function
Generalizing from samples to populations
Predicting probabilities relies on the law of large numbers
Types of probability
o Empirical and theoretical
o Di
Date: Wednesday,
September 26th, 2012
Essential Question:
Key Points:
Levels of Measurement
 Ordinal: unequal distances between ranked categories
Likert Scale
 Interval & ration: equal distances between implied categories. It also has
Ordinal
an absol
Date: Wednesday,
October 3rd, 2012
Essential Question:
Key Points:
Frequency
Distributions
Frequency Distributions
 Order of the values in the frequency tables isnt important if it is with
nominal values
 However, the order of categories is important f
Date: Wednesday,
October 10th, 2012
Essential Question:
Key Points:
Measures of Central Tendency
 Answer the question of what is typical or normal in distribution
Mode

Most frequently occurring value/case
Only CT measure for nominal data (e.g. sources
Date: Wednesday,
October 31st, 2012
Essential Question:
Key Points:
Measures of Variability/Dispersion
 What is atypical?
o Pay attention to the distribution
Range = High value Low value
 Easy to calculate
 Affected by extreme values
Interquartile Rang
Sociology 3H06, 201213 Lecture Summary
Purpose of Social Research
Key Features of the Scientific Method
A process (i.e. a research wheel) based on:
based on observation; collection and analysis of data; i.e. empirical
grounded in theory and larger body o
1. The table below shows the aftertax income for all families in Hamilton
Table: Aftertax Family Income, Hamilton, 2006
Frequency
%
<$20,000
11,595
6.0
Cumulative
%
6.0
$20,000$39,999
$40,000$59,999
$60,000$79,999
$80,000$99,999
$100,000+
34,800
43,
Sociology 3H06, 201213 Lecture Summary
Organizing the Data
Measurement
 Data collected are referred to as variables:
 characteristics that vary across units of analysis
 the specific, empirical measures of concepts
 2 types of variables:
 Independen
Sociology 3H06, 201213 Lecture Summary
Hypothesis Testing & Difference of Means (ttest)
At this point in the course we ask ourselves the following questions:
Is there a relationship between two (or more) variables?
Is the relationship we observe in our
Sociology 3H06, 201213 Lecture Summary
Measures of Central Tendency
Measures of central tendency answer the question of what is typical/common/normal in
a variable (eg. What is the normal income level of Canadians). There are 3 measures
of central tenden