# SOAN 2120 Study Guide - Final Guide: Squared Deviations From The Mean, Null Hypothesis, Standard Deviation

by OC97365

School

University of GuelphDepartment

Sociology and AnthropologyCourse Code

SOAN 2120Professor

David WaltersStudy Guide

FinalThis

**preview**shows page 1. to view the full**5 pages of the document.**Lecture Note Information

Purpose of the Course:

The purpose of this course is to provide an introduction to research methodology in the

social sciences. This class will cover both qualitative and quantitative approaches to

social research.

Quantitative Vs. Qualitative:

Quantitative – applied statistics, numbers

Qualitative – interviews, research, everything else

Experiments Vs. Surveys:

Experiments – very controlled environment – Pretest, Treatment, Post-test

Survey – ask them a number of q‟s – do not manipulate subjects – each question on

survey represents a variable

Types of Variables:

Quantitative Variables – continuous (rank), numerical

(e.g. education… #of years of schooling and income…# money)

Categorical – non-rank order, non-numerical

(e.g. religion… Catholics do not rank higher than protestants and race…skin colour)

Distributions:

When the mean is equal to the median (the average is equal to the middle), this is a

normal distribution.

Normal distributions allow us to conduct significance tests.

The distribution of a variable using data from our sample is called sample distribution.

The distribution of the variable in the population is called population distribution.

The distribution of the mean of a variable from all possible samples is the sampling

distribution.

Sampling distribution – as its standard deviation gets smaller as the size of the sample get

larger.

Sampling distribution – based on calculating a statistic over and over again from sample

samples of the same size.

Measures of Central Tendency:

Mean, Mode, Median, Range

Refresher: mean = average, mode = most occurring, median = middle (when written out

from least to greatest), and range = largest number subtracted by smallest number

Variance/Standard Deviation:

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(N = so in other words, the sample size)

Standard deviation is the square root of the variance.

To calculate the standard deviation:

1) calculate the mean

2) for every observation:

a. first observation minus mean = value. Square that value = new squared

value.

b. Second observation minus mean = value. Square that value = new squared

value.

c. …

d. …

e. last observation minus mean = value. Square that value = new squared

VALUE.

3) Add all the squared values to new a new value (sum of squared deviations).

4) Divide that value by the sample size (n) minus 1.

Validity and Reliability:

(Kayley – go to Brad‟s notes for this – UoG notebook)

Unbiased/Sampling Error:

The difference between the statistic and the parameter due to random process is known as

sampling error.

Random samples have less error than nonprobability samples. The sampling error

decreases as sample size goes up.

Central Limit Theory:

- regardless of the population distribution, with repeated sampling, the shape of the

sampling distribution is approximately „normal‟ (or bell shaped) with the

population parameter at its centre.

- ??

Law of Large Numbers:

- the larger the samples, the more the confidence because it‟s closer to the

population estimate

Z-Scores

- z scores = take „x‟, subtract the mean and divide by the standard deviation

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