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Summary: Applied Statistics I Basic Bivariate Techniques | 9781071807491 | Rebecca M warner
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Read the summary and the most important questions on Applied Statistics I Basic bivariate Techniques | 9781071807491 | Rebecca M. warner
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4 Descriptive Statistics
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4.1 Introduction
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Why can't descriptive statistics not be applied to categorical variables?
Because it doesn't make sense to rank or add scores for categorical variables such as hair color. -
4.2 Questions about quantitative variables
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What is a typical or common response (central tendency)?
The sample mean and median describe central tendency for quantitative varibles -
How much do responses vary or differ?
Additional information about variability is obtained form variance and standard deviation -
4.3 Notation
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What does X1, X2 and X3 mean
Makes clear when a statistic belongs to an individual person -
4.5 Sample mean
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What tricks does the mean illustrates?
It summarize information for a set of scores by summing them up and to correct for the effect of sample size. -
Under what circumstances will the statistic (M) turn out to have a large or small value?
M is large when individual X scores are large and positive. -
4.6 An important characteristic of M: The sum of deviations from M= 0
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What is a deviation from the mean
The distance from the mean -
What happens when you som the deviation mean score?
It will be 0 -
What are the two advantages from the mean?
It's related to many other popular types of statistical analyses and it is the measure of central tendency and most often included in research reports -
4.7 Disadvantage of M: it is not robust against influence of extreme scores
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what makes the mean less robust than the median and mode
Outliers
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