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Chapter 1

PSY201 Chapter 1 Reading.docx

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Department
Psychology
Course
PSY201H1
Professor
Ashley Waggoner Denton
Semester
Fall

Description
Chapter 1 Reading Statistics is facts and figures ex. Birth rate, crime rate, income etc.; condenses large amounts of information into a few figures; set of math procedures for organizing , summarizing and interpreting data  Used to organize and summarize information to effectively and accurately communicate results to help to answer initial question (theory) by providing specific and justifiable conclusions  procedure provides a method that is in unison with other researchers; other people are able to replicate results the same as the original study Population - Sample of scores - the entire group the researcher is interested in ex: study on self esteem of teens with divorced parents. Population would be all teens (study is comparing divorced families and non-divorced families); should always be defined by researcher; can have varying sizes; doesn’t have to be humans Sample - the group of people from the population participating in the study; representatives of the entire population; results from sample are generalized to so they can represent the entire population Variable - specific characteristics and outside factors that can change/influence individuals of the pop./sample; can vary between individuals ex: moods, weather, height, gender, size of room, etc.; characteristics and environmental Data - data set - measurements/observations of the examined variables changing between individuals; measurement per individual referred to as score/raw score/datum Parameter - characteristic of the measurements to describe the population; numerical value of Statistic - characteristic from the measurements to describing the sample; numerical value; used to draw conclusions about population parameters  Descriptive statistics - simplify and summarize data; taking all scores and presenting it a way more manageable ex: graph, average, etc  Inferential statistics - using scores to make general inferences (statements) of the population; job is to determine whether there is probable cause for variation or sample error Sampling error - Margin of error- natural discrepancy between the generalization from the sample to the population, due to limited information from the sample ( cannot account for everyone in sample even as pop. representatives); inferential statistics must always address. Ex: two different samples from the same pop. will have varying result within the parameters  Research is intended to examine relationship between 2 or more variables to prove a relationship exists; it is necessary to observe (measure) the 2 variables; some observing how variables exist naturally by measuring each individual  Correlational method - measuring 2 different variables for each individual to determine if they are correlated; can show a relation but cannot assume that A is because of B (doesn’t provide explanation) due to other possible confounds; some studies may not use numerical values but still must have 2 variables data can be listed in a table displaying how many individuals classified in each possible category, values can be turned into numerical values so they can used for computations but usually used in a chi-square  Experimental/non-experimental methods - determines cause and effect relationship between variables and population; only measures 1 variable; examines relationship between 2 or more groups of scores; uses one of the variables to define the group and measures the 2nd variable to obtain scores for each group and compares them; if systematic difference is apparent there is evidence of relationship o Experimental method - involves manipulation and control to demonstrate cause and effect between 2 variables (changing degree of 1 variable causes changes in 2nd variable);  Manipulation - changing degree of one or more of the variables +/- and measuring effects to 2nd variable to determine if manipulation causes change  Control - exercise control over experimental conditions (environment, extraneous factors) to ensure there is no influence on examined relationship; usually involves control occurrence and uncontrolled (natural/normal) occurrence  To make a cause and effect claim participant and environmental variables have to be considered; random assignment, matching, or holding variables constant are methods of accounting for these variables o Participant variables - individual qualities that vary in each individual ex. age, gender, intelligence,; researchers must account for this when conducting studies and ensure these variables do not greatly differ in groups o Environmental variables -
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