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## monday march 7th notes

1 review
by: Christine Notetaker

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# monday march 7th notes Comm 3000Q

Christine Notetaker
UCONN

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class notes
COURSE
Research Methods in Communication
PROF.
Bryan Vanco
TYPE
Class Notes
PAGES
4
WORDS
KARMA
25 ?

## 1

1 review
"The content was detailed, clear, and very well organized. Will definitely be coming back to Christine for help in class!"
Heber DuBuque

## Popular in Communication Studies

This 4 page Class Notes was uploaded by Christine Notetaker on Tuesday March 8, 2016. The Class Notes belongs to Comm 3000Q at University of Connecticut taught by Bryan Vanco in Spring 2016. Since its upload, it has received 12 views. For similar materials see Research Methods in Communication in Communication Studies at University of Connecticut.

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## Reviews for monday march 7th notes

The content was detailed, clear, and very well organized. Will definitely be coming back to Christine for help in class!

-Heber DuBuque

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Date Created: 03/08/16
COMM 3000Q­004 Page 1 of 4 Problem Set #1 Due after break (3/25 (Friday)) It will be posted this week  you will also need a scientific calculator after break  Exam grades will be up by Friday  Chapter 9: Normal Distribution, Descriptive Statistics and Standard Scores  ­ Raw Data: Numerical data collected from each participant  ­ Data set:  collection of the raw data for the same variables for a set of participants  ­ Statistics:  Any numerical indicator of a set of data  • there are two types:  ­ Descriptive Statistics  • Convey essential information about the data as a whole  • “Describes” patterns in the data  • simple descriptions about the characteristics of a set of quantitative data  ­ Inferential Statistics  • helps us draw conclusions about the population of interest via the sample that we took • also helps us understand relationships between variables  ­ Normal Distribution  • a theoretical distribution of scores in which one side of the curve is a mirror image of the  order  • horizontal axis—all possible values for the variable  • vertical axis—relative frequency at which values occur  • ****in perfect bell curve; the mean, median, and mode all have the same value****  ­ Normal Curve  • There are 5 properties that are associated with a normal curve  1. unimodal  2. mean, median, and mode are all equal  3. symmetrical  4. the range is infinite.  The extreme approach but never touch the X axis  5. the curve is never to peaked, or too flat.  its tails are never too long or too short  ­ Skew (in non­normal distribution)  • the skew of a data set indicates the direction in which it departs from normality  • a measure of symmetry of a distribution  • Skew= (mean­median)/Standard Deviation  ­ mean and median are the same in a normal distribution giving it a skew of “0”  • Positive Skew  ­ Few scores on right side of the curve  ­ mean > median  ­ few extremely high scores  • Negative Skew  COMM 3000Q­004 Page 2 of 4 ­ fewer scores on left side of the curve  ­ Mean < Median  ­ few extremely low scores  • WHEN DISTRIBUTION ARE SKEWED THE MEDIAN IS A BETTER MEASURE OF  CENTRAL TENDENCY  ­ High standard deviation= spread out values  ­ low standard deviation= highly clustered values  ­ Frequency distribution: different distribution shapes  • Normal Distribution  • Bimodal Distribution  ­ why would this happen?  • there isn't an average, there might be two different and smaller populations within the  sample  • something is splitting the sample  • there might be 2 sub samples that are different in a  small way  • • Positive distribution  • Negative distribution  ­ Can also illustrate skews in bar graphs  ­ Kurtosis  • the kurtosis of the distribution indicates the height of the peak  ­ Leptokurtic—scores are tightly around the mean COMM 3000Q­004 Page 3 of 4 23 • “The mean leaps to the middle” • Platykurtic—scores are less likely to be clustered around the mean  24 ­ “flat like a plateau”  ­ 26 the 3 types of descriptive statistics • number of cases  27 27 ­ frequency  • measures of central tendency  27 ­ how did the majority respond  30 • mean  • median  31 31 • mode  • measures of dispersion ­ what is spread of scores from point of central tendency  • rand and standard deviation  ­ Notation used:  • Symbols for descriptions  ­ Sample Size: N or “n” (“n” is used when you are looking at subsamples)  ­ Frequency: f ­ Mean: M or   (x­bar)  • you use x bar when you are comparing groups  ­ Median: Mdn/Md ­ Standard Deviation: SD/ Sd/s ­ Central Tendency  • Mode  ­ the score that appears the most often in the data set (highest frequency)  ­ we commonly see bimodal or multimodal distributions  • which makes it impossible to use the mode to represent central tendency  • example: Exam Scores  ­ in this case 27 is the mode  COMM 3000Q­004 Page 4 of 4 • Median  ­ splits the data set equally in half  ­ when an odd number of data points median is the score in the middle  • when there is an even number of data points the median is the average of the two  points in the middle  ­ not swayed by outliers  ­ referred to as the “visual center” of the distribution  ­ In the example above there is an odd number (9) and the median would be 27 • Mean  ­ Arithmetic average  ­ most commonly used  ­ sensitive to outliers (extreme scores)  ­ mean depends on EVERY score in the distribution  = ���x/N     ­ When there is an ��� it means summation command  • which means that you add whatever come after the ��� which in many cases will be an “x” • x= all the scores in the variable “x”  • N= the sample size

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