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## COMM 2513 Statistics week 3 notes

by: Rachel Notetaker

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# COMM 2513 Statistics week 3 notes COMM 2513

Marketplace > University of Oklahoma > Communication > COMM 2513 > COMM 2513 Statistics week 3 notes
Rachel Notetaker
OU
GPA 3.0
Introduction to Statistics
Johnson

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COURSE
Introduction to Statistics
PROF.
Johnson
TYPE
Class Notes
PAGES
2
WORDS
KARMA
25 ?

## Popular in Communication

This 2 page Class Notes was uploaded by Rachel Notetaker on Saturday September 12, 2015. The Class Notes belongs to COMM 2513 at University of Oklahoma taught by Johnson in Summer 2015. Since its upload, it has received 61 views. For similar materials see Introduction to Statistics in Communication at University of Oklahoma.

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Date Created: 09/12/15
COMM 2513 Statistics Week 3 Normal Distributions A When we look at many variables in the real world many tend to have a normal distribution 1 Normal distributions are symmetrical with 50 of the data on each side No skew Mesokurtic 2 The tallest point on a perfectly normal distribution corresponds to the mean median and mode which are all equal 3 In a normal distribution 68 of the scores fall within one standard deviation from the mean 95 of the scores fall within two standard deviations from the mean 997 of scores fall within three standard deviations from the mean Scores more than 3 standard deviations from the mean are called outliers B There is a special normal distribution called the standard normal distribution 1 This normal distribution has a mean of 0 and a variance and standard deviation of one As long as your original distribution is normal you can transform that distribution into a standard normal distribution Or if you re only looking at one score you can use the standard normal distribution to determine the relative standing of that score Standard score have no units of measurement A Relative standing how one score compares to other scores in the distribution or to characteristics of the distribution such as the mean 1 We can determine this by calculating the zscore Z xmeanstandard deviation If you want to compare two scores from two different distributions you can t just compare the raw scores Zscore 1 A zscore is in units of standard deviations Hence a zscore of 1 means the score designated by X is one standard deviation above the mean A zscore of zero means the score X equals the mean A zscore of 2 means the score X is two standard deviations below the mean Steps for zscore problems A Forwards starts with a score or scores and ends with a percentage 1 Draw picture and shade area trying to nd 2 Calculate zscores 3 Look up critical zscores 4 Find the pvalue of the desired area and change to a percentage To change a pvalue to a percentage multiply by 100 You may have to add or subtract pvalues to get the area of the normal curve that you need B Backwards starts with a percentage and ends with a score or scores 1 Draw picture and designate scores trying to nd with Xs 2 Change percentage to pvalue take percentage and divide by 100 3 Look up pvalue in critical ztable and nd corresponding 2 score ls zscore positive or negative 4 Put zscore into formula and nd X SD 2 mean X 5 Write sentence at end to summarize Use column B when you are looking for the area between your score and the mean Use column C when you are looking for the area between your score and the nearest tail A pvalue tells you the proportion of the area in a section of a normal curve

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