Download presentation

Presentation is loading. Please wait.

Published byKailee Naismith Modified about 1 year ago

1
Density Curves and Normal Distributions Section 2.1

2
Sometimes the overall pattern of a distribution can be described by a smooth curve. This histogram shows the distribution of vocab scores. We could use it to see how many students scored at each value, or what percent of students got 4’s, above 10, etc.

3
Density Curves A density curve is an idealized mathematical model for a set of data. It ignores minor irregularities and outliers

4
Page 79-80

5
Density Curves Page 79-80 0.3030.293

6
Density Curve Always on or above the horizontal axis Has an area of exactly 1 underneath it

7
Types of Density Curves Normal curves Uniform density curves Later we’ll see important density curves that are skewed left/right and other curves related to the normal curve

8
Density Curve Area = 1, corresponds to 100% of the data

9
What would the results look like if we rolled a fair die 100 times? Press STAT ENTER Choose a list: highlight the name and press ENTER. Type: MATH PRB 5:randInt(1,6,100) ENTER Look at a histogram of the results: 2 ND Y= ENTER Press WINDOW and change your settings Press GRAPH. Use TRACE button to see heights.

10
What would the results look like if we rolled a fair die 100 times? 123456 Outcomes 30% or 0.3 20% or 0.2 10% or 0.1 Relative Frequency

11
In a perfect world… The different outcomes when you roll a die are equally likely, so the ideal distribution would look something like this: An example of a uniform density curve.

12
Other Density Curves What percent of observations are between 0 and 2? (area between 0 and 2) Area of rectangle: 2(.2) =.4 Area of triangle: ½ (2)(.2) =.2 Total Area =.4 +.2 =.6 = 60%

13
Other Density Curves What percent of observations are between 3 and 4? Area: (1)(.2) =.2 = 20%

14
Normal curve

15
Density Curves: Skewed Median: the equal-areas point of the curve Half of the area on each side M

16
Density Curves: Skewed Mean: the balance point of the curve (if it was made of solid material)

17
Mean and Median Of Density Curves Just remember: Symmetrical distribution Mean and median are in the center Skewed distribution Mean gets pulled towards the skew and away from the median.

18
Notation Since density curves are idealized, the mean and standard deviation of a density curve will be slightly different from the actual mean and standard deviation of the distribution (histogram) that we’re approximating, and we want a way to distinguish them

19
For actual observations (our sample): use and s. For idealized (theoretical): use μ (mu) for mean and σ (sigma) for the standard deviation. Notation

20
Normal Curves are always: Described in terms of their mean ( µ ) and standard deviation ( σ ) Symmetric One peak and two tails

21
Normal Curves Inflection points – points at which this change of curvature takes place. µ σ Inflection point Concave down Concave up

22
Normal Curves

23
The Empirical Rule The 68-95-99.7 Rule -3 -2 -1 0 1 2 3

24
The Empirical Rule 68% of the observations fall within σ of the mean µ. -3 -2 -1 0 1 2 3 68 % of data

25
The Empirical Rule 95% of the observations fall with 2σ of µ. -3 -2 -1 0 1 2 3 95% of data

26
The Empirical Rule 99.7% of the observations fall within 3σ of µ. -3 -2 -1 0 1 2 3 99.7% of data

27
Heights of Young Women The distribution of heights of young women aged 18 to 24 is approximately normal with mean µ = 64.5 inches and standard deviation σ = 2.5 inches. 62 64.5 67 Height (in inches) 64.5 – 2.5 = 62 64.5 + 2.5 = 67

28
Heights of Young Women The distribution of heights of young women aged 18 to 24 is approximately normal with mean µ = 64.5 inches and standard deviation σ = 2.5 inches. 62 64.5 67 Height (in inches) 59.5 62 64.5 67 69.5 Height (in inches) 5

29
Heights of Young Women The distribution of heights of young women aged 18 to 24 is approximately normal with mean µ = 64.5 inches and standard deviation σ = 2.5 inches. 62 64.5 67 Height (in inches) 59.5 62 64.5 67 69.5 Height (in inches) 99.7% of data

30
Shorthand with Normal Dist. N(µ,σ) Ex: The distribution of young women’s heights is N(64.5, 2.5). What this means: Normal Distribution centered at µ = 64.5 with a standard deviation σ = 2.5.

31
Heights of Young Women What percentile of young women are 64.5 inches or shorter? 5759.5 62 64.5 67 69.5 72 Height (in inches) 99.7% of data 50%

32
Heights of Young Women What percentile of young women are 59.5 inches or shorter? 5759.5 62 64.5 67 69.5 72 Height (in inches) 99.7% of data 2.5%

33
Heights of Young Women What percentile of young women are between 59.5 inches and 64.5 inches? 5759.5 62 64.5 67 69.5 72 Height (in inches) 99.7% of data 64.5 or less = 50% 59.5 or less = 2.5% 50% – 2.5% = 47.5%

34
For homework: 2.1, 2.3, 2.4 p. 83 2.6, 2.7, 2.8 p. 89 Practice

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google