PSY 2730 Quiz 1 Symbols and Terms

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28 Terms

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σ

population standard deviation

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s

sample standard deviation

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summation (sum of all numbers)

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N

population (total number)

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n-1

sample (total number)

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SS

sum of squares

formula:

- find deviations (X - μ)

- square

- sum them up

ex. Data: 2, 4, 6

1. Mean: μ= 2 + 4 + 6 / 3 = 4

2. Find each deviation from the mean: (2−4),(4−4),(6−4) = −2, 0, 2

3. Square each deviation: (−2)^2, (0)^2, (2)^2 = 4, 0, 4

4. Sum the squared deviations: 4+0+4=8

So, SS = 8

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SS formula

SS=∑X^2−(∑X)^2/N

ex. ∑X = 1 + 3 + 5 = 9

∑X² = 1² + 3² + 5² = 1 + 9 + 25 = 35

SS = 35 - 27 = 8

<p>SS=∑X^2−(∑X)^2/N</p><p>ex. ∑X = 1 + 3 + 5 = 9</p><p>∑X² = 1² + 3² + 5² = 1 + 9 + 25 = 35</p><p>SS = 35 - 27 = 8</p>
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weighted mean

- accounts for the contribution of different sample sizes

- calculates the overall mean by summing the values from different groups and dividing by the total number of observations

<p>- accounts for the contribution of different sample sizes</p><p>- calculates the overall mean by summing the values from different groups and dividing by the total number of observations</p>
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σ²

population variance

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sample variance

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variance

squared measure of spread

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standard deviation

- measures the average distance of data points from the mean

- square root of variance

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Z-score

- represented by 'z'

- measures how many standard deviations a data point is from the mean

- positive Z-score = value is above the mean

- negative Z-score = value below the mean

ex. Z-score of 2 means the value is 2 standard deviations above the mean.

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μ

mean of population

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Z-score formula

z = (X- μ)/σ

z=(x-mean)/standard deviation

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M

mean of sample

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descriptive statistics

summarizing data from one group with one or more variables

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correlational methods

examining the relationship between two variables in one group

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comparative methods

comparing two or more groups across one or more variables

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experimental methods

manipulating variables to establish cause-and-effect relationships between them

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non-experimental methods

observing relationship between variables without manipulation

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frequency distribution

a way to organize and summarize data by grouping it into categories or intervals and showing how often each category or interval occurs

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frequencies

number of times a value or range of values appears in the dataset

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class interval

a range of values used to group data in a frequency distribution

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histogram

used for continuous data

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smooth curve

used for large datasets

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bar graph

used for categorical data

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cumulative frequency

add each frequency to the sum of previous frequencies