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Midterm

Psych 1010 midterm 1 study notes.docx

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Department
Psychology
Course
PSYC 1010
Professor
David Stanley
Semester
Winter

Description
Psych 1010 midterm 1 study notes Chapter 1 - Branches of statistics o Descriptive  Organize summarize and communicate numerical information o Inferential statistics  Using data collected from a sample to draw conclusions about a population - Population: set of all observations in a particular study - Sample: A set of observations drawn from a population of interest for inclusion in a study - Parameter: value that described population - Statistic: value that describes sample - Variables o Discrete variables  Can only take on specific values (integers)  Measures how many o Continuous variables  Full range of values  Measures how much o Always discrete:  Nominal variables  Observations with names or categories as values  Qualitative not quantitative differences between categories  Ordinal variables  Ranked by size or magnitude  Know rank but no info about size intervals o Scale variables  Sometimes discrete, sometimes continuous  Interval  Observations of ordered numerical values with intervals of equal size, no meaningful zero  Ratio  Observations of ordered numerical values with intervals of equal size, but there is a meaningful zero  Can form ratios - Operational definition o Set of procedures used to measure or manipulate a variable - Confounding variable o Uncontrolled variable that it unintentionally allowed to vary systematically with the independent variable - Reliability o Consistency of measure - Validity o Extent that the test measures what it is supposed to measure - Research designs o Correlational method  Association between two or more variables  No manipulation, only observation o Experimental method  Randomly assign participants to levels (groups) of the independent variable  Able to make causal conclusions (effect of IV on DV) - Control confounding variables o Random assignment to groups Chapter 2 - Frequency distributions: gives number of times each possible value of a variable occurs in a data set o Frequency table o Grouped frequency table  Used for large range of scores and data to several decimal places  Full range = Xmax – Xmin +1  Use 10 intervals  No gaps o Frequency histograms  Represent scale data (interval and ratio)  Can have polygon overlay (lines over bars) o Frequency polygon  Also represent scale data (looks more like line graph) o Grouped histogram  Use middle of interval at bottom (e.g 7.5 not 0-14.99) o Grouped polygon  Same as histogram, use middle point - Histograms vs. bar graphs o Histograms are used for interval or ratio scales of measurement, bars touch o Bar graph bars do not touch, used for nominal or ordinal data - Normal distribution o Bell-shaped o Symmetrical around the mean o Unimodal (only one peak) - Skewed distributions o Positive skew  tail more to the right  May reflect floor effect (you can’t score any lower) o Negative skew  More to the left  May reflect ceiling effect (you can’t score any higher) Chapter 3 - Misleading with Data o False face validity lie  Method seems to represent what it says, but doesn’t actually (e.g. using yelling as a measure of aggression) o Biased scale lie  Scaling to skew results (e.g. 3 positive words out of 5 options) o Sneaky sample lie  Participants are preselected to provide desired data o Extrapolation lie  Assumes knowledge outside of study (predict things that can not be proven) o Inaccurate values lie  Using scaling to distort portions of the data (e.g. graph about doctors) o Outright lie  Making up data - Graphs o Scatterplot  Show relationship between two scale variables (IV on x and DV on y)  Determine if linear or non-linear relations o Line graphs  Line of bet fit on
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