Research Methods, Week 12 notes
Research Methods, Week 12 notes Psych 305
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This 2 page Class Notes was uploaded by Clarissa Hinshaw on Sunday April 17, 2016. The Class Notes belongs to Psych 305 at Northern Illinois University taught by Keith Millis in Winter 2016. Since its upload, it has received 16 views. For similar materials see Research Methods in Psychlogy at Northern Illinois University.
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Date Created: 04/17/16
Chapter 12 Understanding Research Results: Description Data can be analyzed by comparing group percentages. Ex: examining if race has anything to do with crime. You would investigate the crime rates for each race. Correlations are used to show relationships between variables not tested in experimental groups. Frequency Distribution: the number of people who receive each score on a variable. Pie chart: a chart showing percentages Bar graph: a graph representing each distinct piece of info. Frequency polygon: a graph using a line of best bit. Descriptive Statistics: research describing specific data. Central tendency: explains the overall sample. Mean: average Median: middle number Mode: # occurring most often Variability: the amount of spread in a distribution Standard deviation: deviation of scores from the mean on average. Variance: the square of the standard deviation. Bar or line graphs are most common with variables. Correlation coefficient: a # showing how strong of a relationship two variables have. Pearson productmoment correlation coefficient: used when both variables have scale properties. The correlation shows 2 things: o The coefficient always lies between 1 and 1. The closer to 1or 1, the stronger the correlation. o A positive number shows a positive correlation. A negative number shows a negative correlation. o A scatterplot is used to graph correlations. People in a sample can sometimes be homogeneous. Effect size: the strength of which 2 variables are related to one another. After data results are described the researcher must then state if they found significant results. Regression equation: this is used to predict a person’s variable score. Multiple correlation: many factors contributing to a certain result. Ex: high school grades, ACT score, and letters of recommendation can all predict college success. Third variables can contribute to both variables in a correlation. Ex: time spent on social media can influence both time spent studying and grades received. Partial correlation: a way to help control 3 variables. Path analysis: a diagram showing arrows leading to each variable.
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