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Study Guide For Psych 121 Final

Study Guide For Psych 121 Final - Study Guide for Psych 121...

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Study Guide for Psych 121 Final Outline of all the stuff we read Chapter 8: Descriptive Statistics Introduction Statistic - a numerical representation of information Statistical Methods - to quantify or apply numbers to data in order to organize, summarize, or better understand the information. Simple to Complex Methods Two major branches of statistics each with specific goals and specific formulas Descriptive statistics - refers to the analysis of data of an entire population. Merely using numbers to describe a known data set require the entire population be used i.e. - average test grade of a third grade class. Inferential statistics - two goals: (1) to determine what might be happening in a population based on a sample of the population (often referred to as estimation) and (2) to determine what might happen in the future (often referred to as prediction). To Estimate and Predict a sample of the population is needed Many of the descriptive techniques are also used for inferential data. Scales of Measurement Statistical information - specific qualities (magnitude, equal intervals, and absolute zero) that determine what scale of measurement is being used and therefore what statistical procedures are best.
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Magnitude - the ability to know if one score is greater than, equal to, or less than another score Equal Intervals - the possible scores are each an equal distance from each other Absolute Zero - a point where none of the scale exists or where a score of zero can be assigned 4 scales of measurement are determined from the three scale qualities Ratio – fourth level contains all three qualities. Preferred because data can be easily analyzed Interval – third level, possesses both magnitude and equal intervals, but no absolute zero Ordinal - second level, has magnitude only, can be looked at as any set of data that can be placed in order from greatest to lowest but where there is no absolute zero and no equal intervals Nominal - lowest level, represents only names, has none of the three qualities Types of Distributions Datasets are graphed to form a picture that can aid in the interpretation of the information 3 types of Distributions- Normal, Skew, Kurtosis normal curve - bell shaped, symmetrical, meaning the distribution and frequency of scores on the left side matches the distribution and frequency of scores on the right side The mean, median, and mode of a normal distribution are identical and fall exactly in the center of the curve Skew - how the curve leans. positively skewed - extreme scores on the right hand side of the distribution
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The curve gets pulled in an upward or positive direction.
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