PSYC 2101Exam # 1 Study Guide Lectures: 1 - 6Lecture 1Discourse and Logic• Determine what can be known by reason.• Advantage: skepticism• Problem: lacks data to support conclusionGoals of Psychological Research• Describe behavior• Predict behavior (circumstances)• Explain behavior (determine its causes)• Control behaviorTwo Branches of Statistics1. Descriptive: numbers used to summarize & organize & describe dataEx. mean & median2. Inferential: data from a sample & draw conclusions about a populationWho do we measure?• Population: all individuals we’re interested in• Sample: subset of a populationThe hypo-deductive process• A loop– Theory à Deduction– Deduction à Hypothesis– Hypothesis à Induction– Induction à TheoryLecture 2Statistics and Parameters• Remember samples and populations?– Statistic: values summarizing samples– Parameter: values summarizing populationsRandomness• Random sampling– How we get a sample• Random assignment– Once we have the sample when you’re putting this sample in a groupVariables• Scales of variables1. Nominal2. Ordinal3. Interval4. RatioVariables• Nominal: simple assignments to a categoryEx. gender• Ordinal: ranking; allows more or less judgement but not how much more or lessEx. ranking in a race like 1st, 2nd and 3rd• Interval: ranking with equal intervals between the ranks. Intervals equal across scale• Ratio: interval scale but with a meaningful zero pointEx. time and temperature• Independent (IV): variable you can’t control that get measured• Dependent (DV): variable being controlled• Experiment: Hurry and Helping (Batson et al., 1978)– Question: Does being in a hurry to get somewhere affect our likelihood of helpingothers?Method• Participants began experiment in one building.• After filling out personality measures they were told the rest of the experiment would bein a second building.• ½ were told they were late and had to hurry, ½ were told they had plenty of time to get to the other building• Encountered a man on the floor coughing and groaning• Measured amount of helping, amount of time to travel between buildings.Types of research designs• Experiments • Nonexperiments• Quasi-ExperimentsTypes of experiments• Between subjects• Within subjectsBetween subjects designs• Each level of the IV has one group– Or each participant is in one level of the IV• Benefits: IV causing DV change• Problems: lots of participantsWithin subjects design• Each participant gets each level of the IV• Benefits: less participants• Problems: order effects, testing effects and fatigue effectsLecture 3Why are we talking about graphs?• Graphs are commonly used to convey information– Need to be able to read & create graphs• Reading graphs is a significant portion of the GRE• Graphs can be used to conceal or clarify informationParts of a graph• x axis : horizontal axis (IV)• y axis : vertical axis (DV)• Legend : text in graph• Scale : order of #s along an axisPlotting a single variable• Use a frequency distribution/histogram– x axis : values of the variables of interest– y axis : frequency of occurrence of each value on y-axisStem and leaf displays• Another way to display a single variable – Less popular than histograms (but I’m not sure why)• Define “stems”– Large bins to fit numbers into. Often this is the first digit(s) of each number• Plot “leafs” off each stem. The following digits off the stemShapes of Distributions• Normal: bell curve• Skewed– Positive– Negative• Bimodal and MultimodalGraphs with more than 2 variables• Types of graphs– Scatterplot– Line graph• Time series– Bar graphs• Pareto chart– Pictorial graph– Pie chartLecture 4Scatterplot• Allows you to observe every data point• Mark each axis with the values from a variable– Locate data points within the space based on scores on both variablesLine graphs• Two types– Line of best fit– Time series• Line of best fit• Time series plot• Bar graphs• Used when IV is nominal and DV is continuous• Each bar represents a different level of the IVChoosing the type of graph• What type of variables?– One continuous variable: histogram or stem & leaf– One continuous independent and dependent variable: scatter plot or line graph– One nominal independent and one continuous dependent variable: bar– Two+ nominal independent and one continuous dependent variable: barGuideline for a good graph• Use the same terms as in the body of the text• Avoid chartjunk– Moiré vibrations– Grids– DucksLecture 5Overview• Measures of central tendency• Measures of variabilityDescriptive Statistics• Goal is to explain data:– Organizing data– Central tendency– Variability– Distribution shapeOrganizing Data• Three different ways to visually describe just one variable– Frequency histograms– Frequency table– Grouped frequency tableCentral Tendency• The descriptive statistic that best represents the center of a data set. • Three types of central tendency– Mean: Add up all scores and divide by the number of scores– Median: The middle score of all the scores in a sample when scores are arranged in ascending order– Mode: the most common score in the sampleMeasures of Variability• Everybody does not fit into a measure of central tendency.• How do we represent this?• Measures of variability!Range and Average Deviation• Subtract the lowest score from the highest score• What we want to quantify is how far from the middle of the distribution are the data points?– What if we measure how far each point is from the mean & average #Variance• Average square deviation from the mean• Symbolized by SD^2 or S^2 from a sample• Population would be “sigma squared” o^2 “lowercase sigma”• Problem: in a squared metric which isn’t very useful– To get out of a square, you take the square rootStandard Deviation• The typical amount that scores in a sample vary from the mean• The most commonly used measure of variability• Sample SD is symbolized by SD or S or for a parameter “o”Computing Variance/Standard Deviation1. Calculate the deviations from the mean– The amount that a score differs from the mean of the sample. – Calculate this simply by subtracting each of our individual scores from the mean2. Square each of the deviations from the mean3. Take the average of these deviations, to