Week 2 Flashcards
sampling
the process by which n observations are taken from a population of size N
central tendency
a statistical measure to determine which single score defines the mean of a distribution
population mean
represented by µ
sample mean
represented by M or X-bar
weighted mean
means of 2 groups, overall mean
influencing the mean
- changing a score always affects the mean
- introducing a new score or removing a score will usually change the mean
- adding or subtracting a constant from each score
- multiplying or dividing each score by a constant
when to use mean
when the scores are numerical values, mean is typically preferred
when to use the median
- extreme scores or skewed distributions
- undetermined values
- open-ended distributions
- ordinal scale
when to use the mode
- nominal scale
- discrete variables
- when describing shape
variability
a quantitative measure of the differences between scores in a distribution and describes the degree to which the scores are spread out or clustered
- includes the range, variance, and standard deviation
deviation
the distance from the mean
X - µ = deviation score
the x^2 trick
- removes the negative values
- punishes the larger values
- differences are also squared
- when we square x, we quadruple x^2
variance
the average squared deviation from the mean
standard deviation
the square root of the variance and provides a measure of the average distance from the mean
sum of squared deviations (SS)
the sum of all square deviation scores
biased estimate
sample variability is less than population variability
degrees of freedom (df)
determines the number of scores in a sample that are independent and free to vary and is an adjustment to correct the bias, produces a larger result and makes it an unbiased estimate for population variance
influences for standard deviation
- adding a constant to each score does not change the standard deviation
- multiplying each score by a constant causes the standard deviation to be multiplied by the same constant
