STAT 201 Notes week 9/6-8
STAT 201 Notes week 9/6-8 STAT-201
Popular in General Statistics
Popular in Statistics
This 3 page Class Notes was uploaded by Jessica Namesnik on Saturday September 10, 2016. The Class Notes belongs to STAT-201 at Colorado State University taught by Kirk Ketelsen in Fall 2016. Since its upload, it has received 4 views. For similar materials see General Statistics in Statistics at Colorado State University.
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Date Created: 09/10/16
Statistics 201 9/06/16 Dispersion spread Info about location (avg or median) Range difference between max and min Range=maxmin Positive/right skew mean is pulled to the right, and is larger than the median Negative/left skew mean is pulled to the left, and is smaller than the median Symmetric/bell shaped mean is approximately the same as median IQR= Q Q3 1 is not effected by extreme values b/c os ca;culated using values that lie close to the center of the data set. IQR is not used in inferential statistics but are useful as descriptive statistics Variance another measure of dispersion Closely related to standard deviation. Computed using all the data values in the dataset Sensitive to outliers, but not as effected if there are a large number of values (observations) in the data set. Sum of Standard deviations (“sum of squares” or “ss”) to calc ss for a single observation subtract mean from observation and square the result. Do this for all of the observations and sum the result. ss= Σ(x xx)2 i 2 Sample variance (s )= average squared distance that a group of “n” points lies from the mean of the group(n is # of observations) s = Σ(xi xx)^2 (n1) Sample standard deviation (s) square root of the sample variance. It’s the average distance a group of points lies from the mean. if large, the data is highly dispersed, high level of uncertainty. This is mainly used for statistical inferences. What counts as “large” or “ small” depends on the magnitude of the data itself. s = note( from last week’s homework) variables: quantitative numbers continuous ie weight, any # value discrete ie # of visits to the doctor usually integers, specific # values, no decimals. Qualitativenonnumbers nominal no inherent order. Ie eye color. ordinal inherent order. Ie rank based on preference. ON Thursday no real lecture. Mainly talked about football. Did one practice problem
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