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STAT 201 Notes week 9/6-8

by: Jessica Namesnik

STAT 201 Notes week 9/6-8 STAT-201

Marketplace > Colorado State University > Statistics > STAT-201 > STAT 201 Notes week 9 6 8
Jessica Namesnik

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These notes cover lecture from week 9/6-8
General Statistics
Kirk Ketelsen
Class Notes
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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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