EXERCISE 2.3 Data
Presentation
Objectives
After completing this exercise, you should be able to
1. Explain the difference between discrete and continuous variables and give examples.
2. Use one given data set to construct a line graph.
3. Use another give
Stats: Counting Techniques
Fundamental Theorems
Arithmetic
Every integer greater than one is either prime or can be expressed as an unique product of
prime numbers
Algebra
Every polynomial function on one variable of degree n > 0 has at least one real or
Statistics: Data Description
Definitions
Statistic
Characteristic or measure obtained from a sample
Parameter
Characteristic or measure obtained from a population
Mean
Sum of all the values divided by the number of values. This can either be a population
Population vs Sample
The population includes all objects of interest whereas the sample is only a portion of the
population. Parameters are associated with populations and statistics with samples. Parameters
are usually denoted using Greek letters (mu, si
Chapter 6 Review
Chapter 6 Review #3
Income (1000s)
Probability
Disjoint
A
P(A U B)
P (AB)
Joint/Independent
B
A
Joint/Dependent
B
A
P(A)P(B)
10 29
30 49
50 99
100
0.39
0.24
0.20
0.05
3. (a) P( X > 50,000) = 0.25
B
(b) P (X > 100,000|X> 50,000) = 0.05/0.2
Ch1 2 Review - #1
Class
10 19
20 29
a. Center (median):130.5
Stemplot: 10
Physics Scores
Stem
Chapter
Chapter 1 2 Review - #2 and 3
Frequency
4
6
Cumulative Freq.
4
10
b. A
c. A
Relative Cumulative Frequency
40%
100%
Shape: skewed to right
Leaf
11
6, 8
Sp
Homework 5.61
Homework 5.63, 5.64
(a) Obtain a list of student names in alphabetical order.
Assign a number to each student and randomly select 10
(b) 84%Yes: 01, 02,84
16% No: 85, 86,00
(c)
129
130
131
Y:80% N:20%
36759 58984 68288 22913
YY N N Y YY Y Y
Class Work 5 4:
Treatments: Godiva and Hersheys chocolate
Subjects:
4 female and 4 male students
Directions: use the given information to design three experiments:
1. Completely randomized design; 2. Matched-pairs design, 3. Block design
a) Write an outli
Class work: 4_5 25 Alligators data
Compare 3 models: Round to 4th place
Linear
Exponential
Residuals:
Using Power Law
Model
Power Law
Graph
Log=-4.1764+3.155 log X
LSRL
=310.8948+4.8448x
=100.6351+0.0146x =10-4.1764+3.155logx
1
2
Class work 4_5
Class work
Relationship between 2 variables:
LSRL:
Scatterplot
a is _Intercept
_:
Slope
b is _:
Response
Explanatory
Variable
( X is _ and Y is _)
Variable
Correlation
Units are changed
( stays the same if _ or
X, Y are reversed
_)
When X = 0
When X goes up by 1.
Pu
LinReg
Homework 3.6, 3.9
a= - 41.43
(a) Power boat registrations are explanatory variable.
(b)
Number of manatees killed
Scatterplot: relationship between power boat registrations and number of manates killed
LinReg
3.41
Y=a+bx
Y=a+bx
a=-41.43
b=0.12
b=0.
42 43 46 46 47 48 49 49 50 51 51 51 51 51 52 52 54 54 54 54 54
55 55 55 55 56 56 56 57 57 57 57 58 60 61 61 61 61 64 64 65 68
69
n o i t a r u g u a n I t a s e g A 's t n e d is e r P - t o l p x o B
(b)
Max: 69
65
60
Ages
(a) Mean = 54.8
55
Med =
6.2
Sx
Comparison
Binomial
1.
Binomial
Goal
P (X successes in n trials)
X: # of Successes
Total number of trials
(known)
n
P (X trials takes to get the
first success)
PDF
P(X = a)
X: trials takes to get the
first success
Total number of trials
(unknown)
P
P (suc
Zero product property-for any real numbers a and b if ab=0 then either a=0 or b=0, or both
Quadratic Formula- The solutions of a quadratic equation of the form ax2+bx where a=/= 0, are
given by the following formula
Quadratic Formula
Sum and Product of ro
Shi 1
Simulations
Makes
Misses
Above/Below
26
1.
Simulation 1
20
19
Below
Simulation 2
27
12
Above
Simulation 3
14
25
Below
Simulation 4
12
27
Below
Simulation 5
24
15
Below
Since we are using a six sided die and Shaq had a shooting percentage of 53%, it
Stats: Hypothesis Testing
Definitions
Null Hypothesis ( H0 )
Statement of zero or no change. If the original claim includes equality (<=, =, or >=), it is the null
hypothesis. If the original claim does not include equality (<, not equal, >) then the null
Statistics: Frequency Distributions & Graphs
Definitions
Raw Data
Data collected in original form.
Frequency
The number of times a certain value or class of values occurs.
Frequency Distribution
The organization of raw data in table form with classes and
Stats: Probability
Definitions
Probability Experiment
Process which leads to well-defined results call outcomes
Outcome
The result of a single trial of a probability experiment
Sample Space
Set of all possible outcomes of a probability experiment
Event
On
6851F_ch01_01_25
12/09/2002
06*21 PM
Page 1
1
1.1 (a) The individuals are vehicles (or cars). (b) The variables are: vehicle type (categorical),
transmission type (categorical), number of cylinders (quantitative), city MPG (quantitative), and
highway MPG
3.3I Least Squares
Regression Line
Regression
Define and identify the parts of the
Define
least-squares regression line
least
Warm-Up
Warm
Give an example of an explanatory and a
response variable?
response
Enter the data from pg. 142 ex. 3.24 into L1
and
3.3II Least Squares Regression
Line & Residuals (pg. 167-172)
(cont.)
Review
Correlation, r : measures the direction and
strength of the linear relationship between two
quantitative variables.
2
Coefficient of determination, r : Gives the
percent of the
6851F_ch09_154_160
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18:50
Page 154
9
9.1
2.5003 is a parameter; x
9.2 p
7.2% is a statistic.
9.3 p
48% is a statistic; p
9.4 Both x1
335 and x2
2.5009 is a statistic.
52% is a parameter.
289 are statistics.
9.5 (a) Since the proportion of times the
6851F_ch10_161_172
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19:34
Page 161
10
10.1 (a) 44% to 50%.
(b) We do not have information about the whole population; we only know about a small sample. We expect our sample to give us a good estimate of the population value, but it will not
be exa
Name:_
CP Statistics
Project #2: Analysis of quantitative variables
Due date: A Tuesday November 20th
B Wednesday November 21st
If you cannot hand in your project on time, you will lose 10 points each day.
Project #2 Checklist
POINTS
Each person will col
Name:_
CP Statistics
Project #1: Analysis of categorical variables
Due date: A Friday 9/28
B Monday 10/1
If you cannot hand in your project on time, you will lose 10 points each day.
Project #1 Checklist
POINTS
Each person will collect at least 20 data
(
Class Work 5 4:
Treatments: Godiva and Hersheys chocolate
Subjects:
4 female and 4 male students
Directions: use the given information to design three experiments:
1. Completely randomized design; 2. Matched-pairs design, 3. Block design
a) Write an outli
Class work: 4_5 25 Alligators data
Compare 3 models: Round to 4th place
Linear
Exponential
Residuals:
Using Power Law
Model
Power Law
Graph
Log=-4.1764+3.155 log X
LSRL
=310.8948+4.8448x
=100.6351+0.0146x =10-4.1764+3.155logx
1
2
Class work 4_5
Class work
Godiva & Hershey Experiment
Godiva & Hershey Experiment
Completely Randomized Design
Matched-Pairs Design
Outline: Grouping 2 groups of 4 subjects each
Treatments Godiva chocolate, Hershey chocolate
Compare which chocolate is more popular
Outline: Groupin
Relationship between 2 variables:
LSRL:
Scatterplot
a is _Intercept
_:
Slope
b is _:
Response
Explanatory
Variable
( X is _ and Y is _)
Variable
Correlation
Units are changed
( stays the same if _ or
X, Y are reversed
_)
When X = 0
When X goes up by 1.
Pu