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ISU PSYCH 280 - Methods of Statistics in Social Psychology
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PSYCH 280 1st Edition Lecture 3 Outline of Last Lecture I. Primary Theses of social psychologyII. Empirical v. Intuitivea. AphorismsIII. Hindsight Biasa. Genuine illusion or impression management?IV. Introduction to experimental proceduresa. Operational v. Conceptual definitionsOutline of Current Lecture I. Statistical Abusea. Linear propertiesb. Volume propertiesII. Question Effectsa. Question-Order effectb. Number of Alternatives effectc. Assertion-Agreement effectIII. Random SampleIV. Nature of Statistical DistributionsV. CorrelationsCurrent LectureI. Statistical Abuse“Statistics do not lie—people do.” People use statistics to manipulate others into believing something by using wording and by exploiting the linear and/or volume properties of something. For example, if I want you to believe that four million nickels is a lot of money, I will use linear properties and say: “Four million nickels would reach from sea level to the top of Mt. Everest if they were stacked on top of each other.” If I wanted to make it seem like four million nickels wasn’t a lot of money, I would rely on volumetric properties and say: “Four million nickels would easily fit into a cubical that measured six feet on each side.”- Linear properties are used to exaggerate something (quantity is large)- Volumetric properties are used to downplay something (quantity is small)These notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.Remember: be skeptical when looking at statistics. If you are given only one number, that is not enough—you need to have another number to compare it too.II. Question EffectsQuestion effects refer to phenomenon that the way people answer a question depends on how the question is asked. There are three types of question effects:- Question-Order effect: the order in which questions are asked influences how people answer the different questions- Number of Alternatives effect: as the number of choices increases, the ability of peopleto omit to one single answer decreases- Assertion-Agreement effect: people tend to agree with an assertionBottom line: measuring an opinion is difficult because there are many ways that the questions can be worded in a way that can lead people to give a certain answer.III. Random SampleA random sample is a sample where each member of the population of interest had an equal chance of being chosen for the sample. It is almost impossible to choose a completely random sample, however, so scientists sometimes pick a sample from a population using a technique called stratified random sampling. To choose a stratified random sample from a population, the entire population is split up into group, or strata, based on similar characteristics. Then, a random sample from each group is chosen to make one sample. Note: members are chosen from each strata so that in the final sample, the number of people from each strata is proportional to the number of people in the actual population of interest.IV. Nature of Statistical DistributionsMost statistical distributions follow a normal, or bell curve (see figure below). For a statistical distribution, the x-axis is the measured value (for example, IQ), and the y-axis is the frequency. In a truly normal distribution, all of the central tendency measurements would equal the same value. Central tendency measurements are the mean, the average value of a data set, median, the middle value of a data set, and mode, or the value that appears the most times in a given data set.V. CorrelationA correlation coefficient is a special statistic that has a built in comparison. This statistic reflects the degree of the linear relationship between two variables, x and y. Basically, the correlation coefficient is a measure of how well we can predict y given the variable x. The value of the correlation coefficient ranges from -1.0 to +1.0. A correlation coefficient of +1.0 or -1.0 indicatesa very strong linear relationship between x and y, while a correlation coefficient of 0.0 indicates no linear relationship between x and y (see figures below).- If the correlation coefficient is negative, it does not mean that there is a weak linear relationship between the two variables x and y! A negative correlation coefficient only means that as x increases, y decreases (negative correlation).- If the correlation coefficient is positive, it does not mean that there is a strong linear relationship between x and y. A positive correlation coefficient indicates that as x increases, y also increases (positive correlation). Example of a positive correlation coefficient.Example of a negative correlation coefficient. Example of a zero correlation


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ISU PSYCH 280 - Methods of Statistics in Social Psychology

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