PSY 07202 Study Guide - Comprehensive Midterm Guide: Rowan University, Statistic, Statistical Parameter

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Rowan University
PSY 07202
MIDTERM EXAM
STUDY GUIDE
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Lecture 1: Introduction to Research
The Theory/Data Cycle (also known as Scientific Method)
Theory Research Questions Hypothesis Data ,which either supports
the theory or doesn’t then Repeats
* In Statistics, we will be focusing on the DATA section the most to see whether it
supports or doesn’t support the theory.
Populations & Samples
- Population: a large group that someone is looking to study.
E.g. risky sexual behaviors in adolescents in America then the population
would be ALL of the adolescents in the United States.
- Sample: is the smaller group that you get from the population that you will be
using in your study. Ultimately it’s the subgroup to participate in our study.
E.g. The 100 teens that we give our survey too.
* In research, we have to be careful of how representative the sample is…
meaning does the sample have the same characteristics as the general population.
Representative Sampling
* Need to have the same ratio of characteristics.
Population: 5 yellow, 10 orange, 15 blue
Representative Sample: 1 yellow, 2 orange, 3 blue
How We Use Samples in Research
- Start off with our target Population
- Sample selected from population
- Gather data from the sample
- Results from sample are used to make inferences about pop
Sampling Error
- The naturally occurring discrepancy (or error) that exists between a sample
statistic and the corresponding population parameter.
This is why our samples need to be representative! Even so, it’s not perfect.
Sampling Error (Example)
- Height of female celebrities (in inches) in our population:
List of seven celebrities; Average height in our population: 66 inches (5’6”)
- Let’s take a random sample of 3 celebrities from our population
Chose three random sample of the seven celebrities; Average height in
Sample 1: 66.5” (5’6.5”)
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Chose three random sample of seven celebrities again; Average height in
Sample 2: 67.2” (5’7.2”)
- How do those numbers compare, considering all the average height in our
population, sample 1, and sample 2?
Sampling from the population does not often lead to the exact same number
as the whole population.
Understanding Relationships: Different Research Designs
- The research design is all about how the study is laid out…
How many samples?
How were the variables measured?
How participants are selected & tested?
- Different designs need different statistical procedures to analyze the data
E.g. experiments & correlation
Experimental Basics
- Necessary Components of an Experiment:
1. Manipulation
2. Control
- Experimental/treatment groups: receive the active treatment (ex. two different
kinds of temperature)
- Control groups don’t receive the active treatment
Often get a placebo
Can use a comparison group instead
- Experiments are the only type of research design that supports causal claims!
Can’t determine caulsality with any other research design.
Experimental Variables
- Independent Variable (IV):
Manipulated by the researcher
The researcher chooses the different groups (levels)
- Dependent Variable (DV):
Measured by the researcher
The outcome
What we hope changes based on the independent variable
- Control Variables:
Variables that are held constant controls for confounding variables
Correlation
- Statistical technique used to evaluate association claims
Looks at the linear relationship between two variables
As one variable changes, does the other systematically change with it?
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