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albany - Class Notes - Week 1

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STATISTICAL SUPPLEMENT

1. Psychologists use statistics to make sense of the data they collect

1. ANALYZING THE DATA

1. Statistical analysis allows researchers to discover if their predictions were correct

∙ Raw Data = Actual Scores

2. Descriptive Statistics – uses mathematical procedures in an objective, uniform way to describe different aspects of numerical data (ex. Computing GPA)

3. Inferential Statistics – uses probability theory to make sound decisions about which results might have occurred simply through chance variation

A.Descriptive Statistics

i. Descriptive Statistics – provides a summary picture of patterns in the data

Don't forget about the age old question of What are the four types of biological molecules?

Don't forget about the age old question of What is the galactic plane?

ii. Describes sets of scores collected from one experimental participant (or different groups)

iii. Describes relationships among variables

1. Frequency Distributions

a. Frequency Distribution – a summary of how frequently each of the various scores occurs

b. Step 1 rank-order scores from highest to lowest Step 2 group rank-ordered scores into a smaller number of If you want to learn more check out What is the inferior part of the thorax?

categories (intervals) Step 3 construct a table listing the intervals from highest to lowest

2. Graphs

a. The simplest type of graph is a bar graph

b. Histogram – similar to a bar graph except with number categories instead of name categories

If you want to learn more check out What is the modern development in microbiology?

We also discuss several other topics like What are the four d’s to describe abnormality?

3. Measures of Central Tendency

a. Measure of Central Tendency – a single representative score that can be used as an index of the most typical score obtained by a group of participants

b. Three Different Measures of Central Tendency MODE, MEDIAN, MEAN

c. Mode – The score that occurs more often than any other ∙ Easiest index of central tendency to determine, but least useful

d. Median – a central score (separates upper and lower half of scores)

∙ ODD # OF SCORES = middle number

∙ EVEN # OF SCORES = average of middle numbers

e. Mean – average of ALL scores. Add up all scores and divide by total number of scores

∙ M = ((ΣX)

N )

∙ M: Mean, X: Individual Score, Σ : Summation of What Immediately Follows, N: Total Number of

Scores

f. Unlike the median, the mean IS affected by the specific values of all scores in the distribution

4. Variability

a. Measures of Variability – statistic indicating how tightly the scores in a set of observations cluster together b. Range – simplest measure of variability; difference between the highest and lowest score We also discuss several other topics like Why might scholars not be sure that homer existed?

c. Standard Deviation (SD) – a measure of variability that indicates the average difference between the scores d. You need to know the mean to figure out standard deviation (individual scores also need to be known)

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∙ SD = √Σ( X− M)2

N

∙ (X-M) = individual score minus mean AKA

deviation score

∙ The mean is subtracted from each score, and

each resulting score is squared (to eliminate

negative values)

e. Mean of deviations calculated by summing them up ( Σ ) and dividing by the number of observations (N) [ √ take square root]

f. The larger the standard deviation, the more spread out the scores are

5. Correlation

a. Correlation Coefficient (r) – measure of the nature and strength of the relationship between two variables b. The further a coefficient is from 0 (in either direction) the more closely related the two variables are [higher coefficients permit better predictions of one variable] B.Inferential Statistics

i. Inferential Statistics tells us which inferences we can make from our samples and which conclusions we can legitimately draw from our data

1. The Normal Curve

a. Normal Curve – symmetrical curve that represents the distribution of scores [bell shaped ]

b. The median, mode, AND mean values are the same 2. Statistical Significance

a. Significant Difference – difference between

experimental groups/conditions occurring by chance with a probability of less than 5 out of 100 (p < .05) b. T-Test – analysis of two populations means through the use of statistical examination; combining information about means and standard deviations

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2. BECOMING A WISE CONSUMER OF STATISTICS

1. Large samples are less likely to be misleading than small ones

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