Flashcards in Appendix A & Chapter 1- Introduction Deck (21):

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## Descriptive Statistic

### Produces a number or a figure that summarizes or describes a set of data

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## Inferential Statistic

### A method that uses sample evidence and probability to reach conclusions about unmeasurable populations

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## Population

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All measurements of a specified group

Ex: If you were to have a study on Marian students, and you literally asked each and everyone of the Marian students. There are slim to none studies that are like this though.

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## Sample

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A subset of a population, it may or may not be representative

Ex: If you were doing a study on college students in general and you used Marian students as a sample. They are a small amount of the overall picture of what you are trying to measure

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## Parameter

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A numerical or nominal characteristic of a population

So if you have a study using population you took/have parameters of them

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## Statistic

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A numerical or nominal characteristic of a sample

If you have a study using a sample you took statistics of them

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## Variable

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Something that exists in more than one amount or in more than one form

Example: Height, IQ, dosage, gender, religion, income

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## What are the two different types of variables?

### Quantitative and qualitative

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## Quantitative Variable

### Variable whose levels indicate different amounts. The word quantity is in it. Has a numerical value.

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## Qualitative Variable

###
Variable whose levels are different kinds, not different amounts

Example: 1st, 2nd, 3rd doesn’t tell you how far apart, or by how much they are ranked. It’s qualitative

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## What are the different scales of measurement?

### Nominal, ordinal, interval, ratio

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## Nominal

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A scale in which numbers serve only as labels and do not indicate any quantitative relationship. If you have nominal data you are counting. You count the frequency of ‘oh, how many times do I have this number’. How many fives do I have, how many twos, or threes? You’re counting

Example: football uniform numbers, social security number, phone number

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## Ordinal

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Scale in which numbers are ranks; equal differences between numbers do not represent equal differences between the things measured. Ordinal gives you order.

Example: Rank orders in a race; 1st, 2nd, 3rd place

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## Interval

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Scale in which equal differences between numbers represent equal differences in the thing measured. The zero point is arbitrarily defined.

There’s not a legit zero defined.

I think celsius is ratio though??? Not sure…??

Example: Fahrenheit Temperature

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## Ratio

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Scale with characteristics of interval scale; also, zero means that none of the things measured is present. A lot of psycho social studies do not have zeros, because, for example, if we measured self-esteem no one has a complete zero self-esteem, we all have something. This is not ratio.

Example: Weight, income, dosage

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## What is the only difference between interval and ratio data?

### Ratio has a zero

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## What are the three different kinds of variables?

### Independent, dependent, extraneous

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## Independent Variable

### Variable controlled by the researcher; changes in this variable may produce changes in the dependent variable. What I assume has an effect on the dependent variable. Understand the direction of your experiment.

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## Dependent Variable

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The observed variable that is expected to change as a result of changes in the independent variable in an experiment. What you are measuring, you don’t know what is going to happen with it.

Have to be careful with this one, because there may be things that have or are changing, but we need to make sure they meet the qualifications specified above.

What you assume is getting affected by the independent variable.

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## Extraneous/Confounding Variable

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Variable other than the independent variable that may affect the dependent variable

Stuff that gets in the way of you have completely accurate results. Things that affect your data that you don’t want to, because they are controlled. Crappy designs have extraneous variables.

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