MidtermZochReview

MidtermZochReview - STAT 104 - MIDTERM 1 REVIEW Michael...

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STAT 104 - MIDTERM 1 REVIEW Michael Zochowski 1. Studies Population: entire collection of objects or individuals about which information is desired. Sample: a subset of the population, preferably representative, large, and random. Confounding/Lurking Variable: a variable not included in the study design that does have an eFect on the variables studied. Types of Experiments: see outline 2. Sample Bias: when your conclusions are skewed due to selection, nonresponse, or response biases. 2. Graphs and Data Summary Dotplot: represents each data point for a speci±c variable as a dot above an axis. Scatterplot: a dotplot for two variables. Frequency Table: shows frequency of occurrence of each data group. Histogram: bar graph of a frequency table. Mean: arithmetic average; ¯ x is sample mean, μ is population mean; aFected by extreme values. ¯ x = 1 n ° n i =1 = x 1 + x 2 + ··· + x n n for n data points. Median: the middle number of the data set; if n is even, take the average of the two middle numbers. Less sensitive to extreme values than mean. Skew: when data distribution has a longer tail in one direction; mean tends toward direction of skew. Quartiles: The location of the 25 n %(0 n 4) data point. Whisker Plot: two inner boxes represent 2nd and 3rd quartiles, whiskers represent extent of data. 3. Dispersion: Range: sensitive to outliers, does not reveal distribution. Range = x max x min Interquartile Range (IQR): IQR = 3rd quartile - 1st quartile Maximum whisker length = 1.5 IQR. After this range, a data point is an outlier. Variance: sample is s 2 x , population is σ 2 x s 2 x = 1 n 1 ° n i =1 ( x i ¯ x ) 2 Standard Deviation: s x for sample, σ x for population. s x = ± s 2 x Chebyshev’s Rule: determines the minimum proportion of the data within k standard deviations of the mean. 1 1 k 2 Linear Transformations: Var ( a + bX )= b 2 Var ( X ) Avg ( a + bX )= a + b ( Avg ( X )) Z-Score: z = X ¯ X S X 1
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4. Correlation and Covariance Covariance: describes the direction of a linear relationship between two variables.
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This note was uploaded on 04/05/2012 for the course STAT 104 taught by Professor Stanley during the Spring '08 term at Harvard.

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MidtermZochReview - STAT 104 - MIDTERM 1 REVIEW Michael...

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