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Math 109 Histogram (Chapter 3 Continue) (Lecture 4)

by: tpnguy09

Math 109 Histogram (Chapter 3 Continue) (Lecture 4) Math 109

Marketplace > University of Louisville > Mathmatics > Math 109 > Math 109 Histogram Chapter 3 Continue Lecture 4
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Chapter 3 Histogram
Elementary Statistics
Dr.Prasanna Sahoo
Class Notes
Math, Statistics
25 ?




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This 4 page Class Notes was uploaded by tpnguy09 on Saturday September 3, 2016. The Class Notes belongs to Math 109 at University of Louisville taught by Dr.Prasanna Sahoo in Fall 2016. Since its upload, it has received 4 views. For similar materials see Elementary Statistics in Mathmatics at University of Louisville.

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Date Created: 09/03/16
Review  Controlled experiment as well as observational studies are good methods for collecting data.  However, observational studies are not as successful as controlled experiment.  In a controlled experiment, the investigator decides who will be in the control group and who will be in the treatment group  In an observational study, the subjects assign themselves to one of these two groups. o The studies on  The effect of smoking  The sex discrimination on graduate admission  The racial discrimination in work place  The effect of spanking a child (can lower IQ  Are some examples of observational studies o In any observational study, confounding is a major source of bias o To avoid the effects of hidden confounding factors statisticians make comparisons separately for smaller and more homogenous groups  Compare gender to gender or age to age o In the UC, Berkeley example, we have seen that although the graduate school admitted 44% male applicants and 30% female applicants, the admission rate was because of the choice and not because of sex discrimination.  Compare major to major  Women decided to take harder majors than man Chapter 3  In 1973, fifty thousand American families were asked to report their incomes for the year 1972. The U.S. government received 50,000numbers o How do we examine and make sense out of 50,000 numb3ers? o Answer: summarize them. o To summarize data, statisticians often use a graph called a histogram.  A histogram consists of a set of blocks.  The ranges are called the class intervals  A histogram represents numbers by area, not height  The area of a block represents the percentage of the data that fall into the corresponding class interval.  Find the block u want, then do H x W  Reading a histogram o To learn how much data lies b/t two values, shade in the area above these values on the given histogram and estimate the area of the histogram that is shaded o Sometimes can draw curve (sketch) o If no vertical scale is given, estimate the area  How to draw a histogram o  Density Scale  A histogram is said to be in density scale if; o The height of each block is equal to the percentage of the data in that block divided by the width of that block o The units on the vertical axis are given in “% per horizontal unit” and o The total area of the histogram is 100%  If a histogram is in density scale, then, “lots of area implies lots of data points”  If a histogram is in the density scale, then the height of the histogram shows the crowding


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