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by: Emma Natzke

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# Chapter 1 Notes PSY 230

Emma Natzke
ASU
GPA 3.4

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Chapter 1 notes for Introductory Statistics with Professor Branaghan
COURSE
Introduction to Statistics
PROF.
Prof Branaghan
TYPE
Class Notes
PAGES
3
WORDS
CONCEPTS
Statistics, PSY230
KARMA
Free

## Popular in Psychlogy

This 3 page Class Notes was uploaded by Emma Natzke on Wednesday May 18, 2016. The Class Notes belongs to PSY 230 at Arizona State University taught by Prof Branaghan in Spring 2016. Since its upload, it has received 4 views. For similar materials see Introduction to Statistics in Psychlogy at Arizona State University.

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Date Created: 05/18/16
Statistics serve two general purposes: 1. To organize and summarize information so that researchers can see what happened in the research study and communicate the results to others. 2. Help researchers answer the questions that initiated the research by determining exactly what general conclusions are justified based on the obtained results. Statistics - a set of mathematical procedures for organizing, summarizing, and interpreting information. Population - the set of all the individuals of interest in a particular study. Sample - a set of individuals selected from a population, usually intended to represent the population in a research study. • Intended to be representative of its population • Should always be identified in terms of the population from which it was selected. Variable - a characteristic or condition that changes or has different values for different individuals. Parameters describe populations while statistics describe samples. • Descriptive statistics - statistical procedures used to summarize, organize, and simplify data • Inferential statistics - techniques that allow us to study samples and then make generalizations about the populations from which they were selected. Sampling error - the naturally occurring discrepancy, or error, that exists between a sample statistic and the corresponding population parameter. Experimental method – comparing groups of scores. One variable is manipulated while the other is observed and measured. • Manipulation – changing the value of a variable from one level to another. • Control – ensure that other variables do not influenced the relationship being examined. • Variables o Participant variables – age, gender, and intelligence that vary from one individual to another. o Environmental variables – characteristics of the environment such as lighting, time of day, and weather. o Independent variable – manipulated by the experimenter. o Dependent variable – variable that is observed and measured to obtain scores within each condition. o Control condition – does not receive experimental treatment or a placebo treatment. Provides a baseline for comparison with the experimental condition, which does receive the treatment. Nonexperimental methods – examine the relationship between variables by comparing groups of scores. • Nonequivalent groups – comparison by biological factors that cannot be manipulated (age, gender, etc.) • Pre-post study – comparing scores before an after a stimulus. What happens between those times cannot be controlled. o Independent variable in these methods is called quasi-independent. Constructs – internal characteristics that cannot be directly observed. Operational definition – defines a construct in terms of external behaviors that can be observed or measured. • Variables o Discrete variable – separate, indivisible categories. No values can exist between two neighboring categories. Commonly restricted to whole, countable numbers. o Continuous variable – when there are an infinite number of possible values that fall between to observed values (height, weight, time, etc.) § It should be very rare to obtain identical measurements for two different individuals. § Each measurement category is actually an interval that must be defined by boundaries. (i.e. two participants who claim to be 150 lbs are actually 149.9 and 150.3) • Real limits are the boundaries of intervals for scores that are represented on a continuous number line (upper and lower). Nominal scale - classifying individuals into categories that have different names but are not related to each other in any systematic way. Ordinal scale - a set of categories that are organized in an ordered sequence. Measurements on an ordinal scale rank observations in terms of size or magnitude (i.e. small, medium, or large sodas). Interval scale – measurement by units while using 0 as a reference. Ratio scale – measurement by units while using 0 to represent the absence of said units. With a ratio scale, ratios of numbers do reflect ratios of magnitude. Representing Data: • X = variable 1 • Y = variable 2 (optional) • N = number of scores in a population • n = number of scores in a sample • Σ = the sum of o It’s always followed by a symbol or mathematical expression. § Σ(X-1)^2 à calculate all (X-1)^2 values and add results. o Order of operations 1. Parentheses - PEMDΣAS 2. Exponents 3. Multiplication/division 4. Summation process of the Σ 5. Addition/subtraction I.e. ΣX^2 à square all values of X, then find the sum of the squared values.

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