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The Practice of Statistics Third Edition Chapter 2: Describing Location in a Distribution Section 2.1 Measures of Relative Standing and Density Curves.

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Presentation on theme: "The Practice of Statistics Third Edition Chapter 2: Describing Location in a Distribution Section 2.1 Measures of Relative Standing and Density Curves."— Presentation transcript:

1 The Practice of Statistics Third Edition Chapter 2: Describing Location in a Distribution Section 2.1 Measures of Relative Standing and Density Curves Copyright © 2008 by W. H. Freeman & Company Daniel S. Yates

2 Objectives What are measures of relative standing? What is a Standardize Value? How do you compute a z-score of an observation given the mean and standard deviation of a distribution? What does the z-score measure? How do you find the pth percentile of an observation in a data set? What is a Mathematical Model? What is a Density Curve?

3 Measures of Relative Standing Suppose we have a data set of grades for Algebra 2AB Chapter Test : ( 94, 61, 40, 72, 73, 88, 68, 62, 73, 57, 35, 82, 48, 66, 65, 79, 45, 91, 66, 71, 63, 11, 69, 64, 38, 59, 70, 70, 79, 77, 39, 55) We can discuss a particular students grade relative standing in the class in two ways: – Relative to the median (percentile) – Relative to the mean (how far way from the mean)

4 p th Percentile Pth percentile of a distribution – the value with p percent of the observations less than or equal to the observation in question. For example we are interested in the percentile for a test grade of 45. Data sorted: (11,35, 38, 39, 40, 45, 48, 55, 57, 59, 61, 62, 63, 64, 65, 66, 66, 68, 69, 70, 70, 71, 72, 73, 73, 77, 79, 79, 82, 88, 91, 94 ) 6/32 x 100 = 18.75%

5 Your turn! Data sorted: (11,35, 38, 39, 40, 45, 48, 55, 57, 59, 61, 62, 63, 64, 65, 66, 66, 68, 69, 70, 70, 71, 72, 73, 73, 77, 79, 79, 82, 88, 91, 94 ) What is the percentile for a grade of 66? 17/32 x 100 = 53.1% What is the 50% percentile? Grade of 66.

6 Relative to the Means of the Data Set We standardize each data by: The standard value (z-score) is a measure of how many standard deviations a data value is from the means of the data set.

7 Back to Our Example Data sorted: (11,35, 38, 39, 40, 45, 48, 55, 57, 59, 61, 62, 63, 64, 65, 66, 66, 68, 69, 70, 70, 71, 72, 73, 73, 77, 79, 79, 82, 88, 91, 94 ) What is the standard value for a test grade of 45? First we need to find the mean and standard deviation. Mean = and S x = What is the z-score for a grade of 66? z = 0.144

8 Calculator Exercise We will convert all the grades to z-score. Data sorted: (11,35, 38, 39, 40, 45, 48, 55, 57, 59, 61, 62, 63, 64, 65, 66, 66, 68, 69, 70, 70, 71, 72, 73, 73, 77, 79, 79, 82, 88, 91, 94 )

9 Impact on the Distribution When we Standardize We need to look at the mean and standard deviation, to find out what is the impact. Recall: Linear Transformation: x new = a + bx When we add (or subtract) a constant from each data we move the distribution by that amount but we do not change the spread. When we multiply (or divide) each data by a constant we change the spread. We can quickly compute the new standard deviation by multiplying the old standard deviation by dividing it by the constant.

10 Impact Continued So looking at the formula to convert data to a standard value we can see we are moving the distribution by a constant and by dividing the standard deviation we are changing the spread. If x = mean, then mean – mean = 0. The new mean is 0. By dividing by the standard deviation we are changing the standard deviation to 1 since

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12 Data Analysis Toolbox (p123) When describing a distribution – 1.Always plot the data. 2.Look for overall pattern (shape, center, spread) and striking deviations such as outliers. 3.Calculate a numerical summary to describe center and spread. 4.For large data sets, can we fit a smooth curve to the distribution.

13 For Example The smooth curve are an idealized description (mathematical model) for the distribution. Smooth curves are easier to work with than histograms

14 Density Curves When we adjust the scale so that the area underneath the curve is one we have density curve. Definition :

15 Density Curves Density Curves come in different shapes, but they all have the same area of 1.

16 Density Curve Parameters Since density curves are idealized descriptions of the data distribution we use different symbols to represent: Sample Density curve Mean µ Standard Deviation SxSx σ

17 Algebra 2 Grades

18 The Median and Mean of a Density Curve

19 Problem 2.12 page 128 (a) Mean C, Median B (b) Mean A, Median A (c) Mean A, Median B

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