Learning_goals_part1

Learning_goals_part1 - Psych 100 A Learning Goals for Exam...

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Psych 100 A Learning Goals for Exam 1 LEARNING GOALS FOR EXAM 1: Describing Data, Statistical Inference, Z-tests and One-Sample T-tests. I. DESCRIBING DATA I-A. INTRODUCTION AND BASIC CONCEPTS . (Reading: Kiess Chapters 1 & 2) Learning statistics is like learning a language. You must become fluent in the basic vocabulary. You should understand: That measurement assigns numbers to variables. You should be able to: Define and understand the differences between: sample vs population independent variable vs dependent variable Recognize and give examples of the four levels of measurement: nominal (qualitative) ordinal interval ratio. Recognize and give examples of the two types of variables: discrete continuous. I-B. DISTRIBUTIONS OF SCORES . (Kiess Ch 3) A major goal of this section is to learn that the first step in data analysis is to examine the frequency distributions—the distributions of scores for each variable. You should understand: The relationship of empirical distributions of data to theoretical distributions of data (statistical models). The relationship of an individual score to a distribution of scores. 1
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Psych 100 A Learning Goals for Exam 1 The differences between: a simple frequency distribution, a relative frequency distribution, and a cumulative relative frequency distribution, And be able to recognize situations when one is preferable to the others. That changing the class intervals of a histogram can reveal different characteristics of the distribution. The difference between the stated limits and real limits given a class interval You should be able to: Use the distribution of scores to help understand the processes that generate the data. Detect, given a distribution of scores, errors, outliers and score spreads. Construct, by hand, the rank order of the scores, data tables, ungrouped frequency distributions, grouped frequency distributions, histograms, from a set of scores Make inferences about the shape of the distribution from a boxplot. Characterize a distribution by its shape, middle and spread.
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This note was uploaded on 09/24/2010 for the course STATS 13a taught by Professor Chen during the Spring '10 term at UCLA.

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Learning_goals_part1 - Psych 100 A Learning Goals for Exam...

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