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## Statistics in Psychology Exam 1 Study Guide

by: Athena Manzino

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# Statistics in Psychology Exam 1 Study Guide PSYC 20700

Marketplace > Ithaca College > Psychlogy > PSYC 20700 > Statistics in Psychology Exam 1 Study Guide
Athena Manzino
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Study Guide Exam 1
COURSE
Statistics In Psychology
PROF.
Ann L. Lynn
TYPE
Study Guide
PAGES
5
WORDS
KARMA
50 ?

## Popular in Psychlogy

This 5 page Study Guide was uploaded by Athena Manzino on Saturday February 13, 2016. The Study Guide belongs to PSYC 20700 at Ithaca College taught by Ann L. Lynn in Spring 2016. Since its upload, it has received 44 views. For similar materials see Statistics In Psychology in Psychlogy at Ithaca College.

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Date Created: 02/13/16
Statistics in Psychology Exam 1 Study Guide Definitions:  Population: o Everyone you want to generalize the results of the study to (N)  Sample: o A subset of population (n)  Variable: o Characteristic expected to change/differ across individuals  Constant: o Characteristics expected to be the same across individuals  Independent variable: o Predictor variable, expected to influence dependent variable  Dependent variable: o Outcome variable  Construct (conceptual variable): o Abstract description of a variable/characteristic  Operational variable: o (Operationalize) description of specific way variable will be observed (ex. Hours/temperature/length)  Experimental study: o Researcher manipulates independent variable (want random assignment/can draw a causal conclusion)  Observational study: o No manipulation- measure and observe natural habits, IV and DV measured, no causal conclusion  Parameter: o Value that describes a population, use Greek symbols  Statistic: o Value that describes a sample, use roman letters (mean=M, SD=S, correlation coefficient=r)  Inferential statistics: o Use sample data to draw conclusions of population  Descriptive statistics: o Procedure that allows you to summarize, organize, and simplify data  Mean: o Average of the data set  Median: o Middle number in the set  Mode: o Most frequently occurring value  Standard deviation: o Average difference between each value and mean  Range: o The difference between the highest and lowest variable (must have quantitative data)  Outlier: o Extreme observation, doesn’t fit with the data set  Kurtosis: o Describes variability of frequency distribution  Skew: o Describes symmetry of a frequent distribution  Leptokurtic: o Graph with the smallest standard deviation (skinny graph)  Platykurtic: o Graph with the largest standard deviation (graph looks like a plateau)  Categorical: o Measure with a fixed number of values/categories  Quantitative: o Value indicates measureable quantity  Nominal: o Uses numbers as labels, categorizes the objects being measured  Ordinal: o Rank order the objects according to whether they have more, less or the same amount of the variable being measured  Approximate interval: o “Likert type” scales assumed to be near enough to interval to be treated as interval  Interval: o Numerically equal distances on scale represent equal distances on the dimension being measured  Ratio: o Possess all above characteristics, and have a meaningful zero Identify:  Types of Measurement o Categorical  Has fixed values  Made of categories  Ex. Gender or flavor of ice cream o Quantitative  Values have a measurable quantity  Ex. Frequency of attendance  Scales of Measurement o Nominal:  No math  No order  Ex. Religious affiliation  Categorical o Ordinal  No equal intervals just order  Ex. In a race (different times between different places)  Ex. Rankings in the army but don’t have specific values in between  No math o Approximate interval  Measure of what people like  Ex. To what extent do you like ice cream (on a scale of 1 to 10)  Use math o Interval  Equal intervals  Zero is arbitrary  Ex. Temperature, each degree change is equal throughout scale but, in Fahrenheit and Celsius “0 degrees” is different and just a made up point  Could be used for IQ tests or SAT tests o Ratio  Has order  Equal intervals  Absolute zero  Ex. In temperature, when it’s zero degrees Kelvin, zero means the absence of heat (no negative numbers like in Fahrenheit and Celsius)  How much/many  Ex. Spelling test (graded on how many words you spell correctly)  Independent variable (ID) vs. Dependent variable (DV) o Dependent variable changes based on the independent o Independent stays the same despite the dependent variable o Ex. People who smoke (ID) vs. test scores (DV)  Skew o Positive  Tail is on the high end of the graph  Ex. Most people did poorly on a test o Negative  Tail is on the low end of the graph  Ex. Most people did well on a test  Kurtosis o Platykurtic  Mean doesn’t fully capture accurate data  Large standard deviation  Plateau shaped graph o Leptokurtic  Small standard deviation  Most drastic data set  Narrow shaped graph  Greek symbols o Population (μ) o Σ (sigma)= means sum of o Sample=σ (lowercase sigma) o Mean= χ  Roman symbols o Mean=M o Standard Deviation=SD o Correlational Coefficient=r o Sum of squares= SS o Sample=S Apply, Compare, Contrast  Central tendency o Mode  Use for nominal data  Can report from nominal to ratio o Bimodal  Two equal modes  Report both o Multimodal  More than two equal modes  Report all modes o Median  Middle number of set  50% above 50% below  Can be used for ratio, approximate interval, and interval  Reorder data o Mean  Quantitative data  Influenced by outliers  Variability o Range  Distance between largest and smallest score in a distribution  Quantitative data o Standard deviation  Average difference between each value and mean  Shows the accuracy of the mean Interpret  Mean o Ex. On average, students scored an 85 on the test  Standard deviation o Ex. “On average, students scored an 85 on the test plus or minus 5 (SD)” Computational Sample data: Person Grade Bill 3 Sookie 4 Eric 6 Sam 3 Tara 2  Mean o 3+4+6+3+2=18 o 18/5=3.6  Median o 2,3,3,4,6 o 3  Mode o 3  Range o 6-2+4

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