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Psychological Statistics Midterm: Key Concepts and Measures, Exams of Psychology

A.T. Still University of Health Sciences (ATSU)Psychology

An overview of essential statistical concepts and measures used in psychological research. Topics include the difference between populations and samples, parameters and statistics, sampling error, research methods, scales of measurement, frequency distribution, measures of central tendency, and skewness. Additionally, it covers the concepts of negative and positive skew, standard deviation, z-scores, and hypothesis testing.

Typology: Exams

2023/2024

Available from 04/12/2024

DrShirley
DrShirley 🇺🇸

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Psychological Statistics Midterm
Population -
The entire group of interest
Sample -
The subset of individuals selected from the population
Parameter -
The characteristic/value that describes a population
Statistic -
The characteristic/value that describes a sample
Sampling Error -
The discrepancy between a sample statistic and the corresponding population parameter
Research Methods -
Experimental Methods (Comparing Groups) Independent Variable- Manipulated in an
experiment, and causes changes in DV
Dependent Variable- Outcome measured in experiment and "depends" on IV
Control Condition- Non-treated group; provides a baseline
Experimental Condition- Gets experimental treatment/intervention
Non-Experimental Methods (Comparing Groups)
Non-equivalent Groups- No IV manipulation, Pre-Existing Groups
Pre-Post Studies- No control group and the same group measures before (pre) and after (post)
intervention/treatment
Scales of Measurement -
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Psychological Statistics Midterm

Population - The entire group of interest Sample - The subset of individuals selected from the population Parameter - The characteristic/value that describes a population Statistic - The characteristic/value that describes a sample Sampling Error - The discrepancy between a sample statistic and the corresponding population parameter Research Methods - Experimental Methods (Comparing Groups) Independent Variable- Manipulated in an experiment, and causes changes in DV Dependent Variable- Outcome measured in experiment and "depends" on IV Control Condition- Non-treated group; provides a baseline Experimental Condition- Gets experimental treatment/intervention Non-Experimental Methods (Comparing Groups) Non-equivalent Groups- No IV manipulation, Pre-Existing Groups Pre-Post Studies- No control group and the same group measures before (pre) and after (post) intervention/treatment Scales of Measurement -

N.O.I.R.

Nominal Scale- Categories that have different names and No quantitative distinction between categories

  • Ordinal Scale- Categories organized in ordered sequence and No information about distance between categories Interval Scale Categories are intervals of exactly the same size and the Zero point is arbitrary Ratio Scale- Interval scale with absolute zero Frequency Distribution - Every score from a measurement scale, has a number of individuals receiving that score, and how often the number appears. In a graph f=frequency Proportions (Frequency Distribution) - Fraction of total group associated with score p=f/N (proportion=frequency/number) Percentages (Frequency Distribution) - The standardized fraction with 100 as denominator. p(100) = f/N(100) (frequency/number) (100) Cumulative Percentages (Frequency Distribution) - cf/N x 100 (Cumulative Frequency/Number Total)(100) Mean - The sum of scores, divided by number of scores. Median - Scores are listed in order of magnitude, and it is the middle score in distribution Mode - The score/category with the greatest frequency, and it is identified using frequency distribution.

A statistical method that uses sample data to evaluate a hypothesis about a population. Type I Error - Reject Ho when Ho is true, falsely concluding the treatment has effect. (false positive) Type II Error - Fail to reject Ho when Ho is false, falsely concluding the treatment has no effect (false negative) Alpha - Probability of obtaining data in critical region if Ho is true. α = Probability of Type 1 Error. Critical Region - Sample means that are unlikely if null-hypothesis is true.