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MATH 131
Formulas for Test 3
Confidence Intervals:
o s
E=Zc- E=tc E=Z H
J; n c n
2
Sample Size: n = [Zcoj
E
Testing Hygothesis: Z = Y-H t: 35
0' S
J; J;
2
Chi-Sguare: II = 2%
Goodness of Fit Test
E. = npl. where n is the number of trials
MATH 131
8/11
TEST 2 REVIEW SHEET
Links to pencast solutions to selected problems are boxed next to these problems. Written answers to all
problems can be found at the end of the review sheet.
Important terms and phrases: To locate these terms in the book
MATH 131
TEST 3 REVIEW SHEET
8/11
Important terms and phrases: To locate these terms in the book, please use the index at the
back of the book.
c, level of confidence
Critical values
E, Margin of Error
Confidence interval
n, minimum sample size
t-distribu
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MATH 131
Formulas for Test 2
Multiplication Rule
If events A and B are independent, then
P A and B P A P B
If events A and B are dependent, then
P A and B P A P BA
Addition Rule
If events A and B are mutually exclusive, then
P A or B P A P B
If
MATH 131
8/11
TEST 1 REVIEW SHEET
Links to pencast solutions to selected problems are boxed next to these problems. Written answers
to all problems can be found at the end of the review sheet.
Important terms and phrases: To locate these terms in the book
Math 131
Test 3 Study Guide
Page 1 of 12
Math 131
Test 3 Study Guide
1. A teacher wanted to see the relationship between number of absences and performance in the
course. She collected a small data set from her students last semester.
Scatter Plot
Number
MATH 131
Test 2 Study Guide
1. The probability that a person in the United States has type AB positive blood is 8.61%. Three unrelated
people in the United States are chosen at random.
a. Find the probability that all 3 have type AB positive blood.
Answer
UNIT 3 SUMMARY CONFIDENCE INTERVAL AND HYPOTHESIS TESTING
Confidence Interval
For Population mean()
n > 30
Hypothesis Testing(always state
For Population
Proportion(p)
n < 30
For Population mean()
Chi-Square
Large samples
n > 30
Ho :
Small samples
n < 30
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MATH 131
Formulas for Test 1
Formula for Mean
From raw data
x
x
n
(where n f )
From a frequency distribution
x
or
x
N
x f
n
Formula for Standard Deviation
From raw data
s
(x x)
2
n 1
or
(x )
N
From a frequency distribution
s
2
(x x) f
n 1
Standa
MATH 131
8/16
Lab 2
Kelly Williams
The goal of this lab is to organize your data from Lab 1 into frequency distributions and graphs.
Graphs should be made by hand, using a ruler.
Part 1: V1, Qualitative Data
(3 points)
A. Prepare a frequency and relative
MATH 131 Unit 2
Class Activity 1
8/16
Data from the World Health Organization represents countries in terms of poverty and life
expectancy in the following table.
Percentage of Country Living in Poverty
Divided at 30% of country in poverty
Life Expectancy
Math 131
Section 2.4
Section 2.4 Measures of Variation
Determine the range of a data set
Determine the variance and standard deviation of a population and of a sample
Use the Empirical Rule and Chebychevs Theorem to interpret standard deviation
Approx
Math 131
Section 1.3
Section 1.3 Experimental Design
Discuss sampling techniques
Section 1.3
Page 1
Section 1.3 Experimental Design
Sampling Techniques
A sampling is a count or measure of part of a population, and is more commonly used in
statistical stu
Math 131
Section 7.3
Section 7.3 Hypothesis Testing for the Mean (Small Samples)
Find critical values in a t-distribution
Use the t-test to test a mean
Use technology to find P-values and use them with a t-test to test a mean
Section 7.3
Page 1
Findi
Math 131
Section 2.3
Section 2.3 Measure of Central Tendency
Determine the mean, median, and mode of a population and of a sample
Determine the weighted mean of a data set and the mean of a frequency distribution
Describe the shape of a distribution as
Math 131
Sections 3.3 & 3.4
Section 3.3 The Addition Rule
Determine if two events are mutually exclusive
Use the Addition Rule to find the probability of two events
Section 3.4 Additional Topics in Probability and Counting
Determine the number of ways
Math 131
Section 10.2
Section 10.2 Independence
Contingency Tables
o
o
o
o
Cell
Marginal Frequencies
Sample size
Finding Expected Frequencies
The Chi-Square Test for Independence
o Performing a Chi-Square Independence test
o Using Technology for a Chi-S
Math 131
Section 9.1
Section 9.1 Correlation
Overview of Correlation
o
o
o
o
Bivariate data
Dependent and Independent Variables
Correlation
Scatter Plot
Positive, Negative, and No Linear Correlation
Correlation Coefficient
Using a Table to Test Popula
Math 131
Section 7.1
Section 7.1 Introduction to Hypothesis Testing
Hypothesis Test
Stating a Hypothesis
o The Null and Alternative Hypothesis
Types of Errors and Level of Significance
o Type I and II Errors
o Identifying Type I and Type II errors
o Le
Math 131
Section 10.1
Section 10.1 Goodness-of-Fit
2
The Chi-Square Goodness-of-Fit Test
o
o
o
o
o
o
Section 10.1
Multinomial Experiments
Category Data
Observed Frequency O
Expected Frequency E
The Chi-Square Goodness-of-Fit Test
Performing a Chi-Square
Math 131
Section 2.5
Section 2.5 Measures of Position
Determine the quartiles of a data set
Determine the interquartile range of a data set
Create a box-and-whisker plot
Interpret other fractiles such as percentiles
Determine and interpret the standard s
Math 131
Section 7.2
Section 7.2 Hypothesis Testing for the Mean (Large Samples)
Using P-values to make Decisions
o Decision Rule Based on P-value
o Finding a P-value for a Hypothesis Test
Left-Tailed, Right-Tailed and Two-Tailed Tests
Using P-values f
Math 131
Section 2.1
Section 2.1 Frequency Distributions and Their Graphs
o Constructing a Frequency Histogram (Broken axis)
Broken Axis
With Class Boundaries
With Class Midpoints
o Constructing Relative Frequency Histograms
Broken Axis
With Class Bo
Math 131
Section 9.2
Section 9.2 Linear Regression
Find the equation of a regression line
Predict y-values using a regression equation
Section 9.2
Page 1
Regression lines
After verifying that the linear correlation between two variables is significant,
Math 131
Sections 1.1, 1.2
Breakdown of Courses
Unit
1
2
3
Model
Descriptive (Basic) Statistics
Probability & Probability Distributions
Inferential Statistics
Chapters
1&2
3, 4, & 5
6, 7, 9, & 10
1. Descriptive Statistics is the branch of statistics that
Math 131
Section 3.1
Section 3.1 Basic Probability Concepts and Counting
Identify the sample space of a probability experiment
Identify simple events
Use the Fundamental Counting Principle
Distinguish among classical probability, empirical probability
Math131
Section 3.2
Section 3.2 Conditional Probability and the Multiplication Rule
Determine conditional probabilities
Distinguish between independent and dependent events
Use the Multiplication Rule to find the probability of two events occurring in
Math 131
Section 2.2
Section 2.2 More Graphs and Displays
Graph quantitative data using stem-and-leaf plots
Graph qualitative data using pie charts and Pareto charts
Section 2.2
Page 1
Graphing Quantitative Data Sets
Stem-and-leaf plot
Each number is s
Christina Apuzzo
Statistics 131
Lab One
23 February 2016
1. The question I am answering in my study is if the type of dog affects how long until they
are adopted. I anticipate finding if the breeds weight creates correlates with the amount
of years spent
Exam Guideline
*Show all your work*
1.
The percentage of unemployed workers in each of 20 randomly selected cities
are as follows:
3.1
5.4
4.5
3.8
8.2
7.2
1.4
3.8
6.3
4.6
1.8
7.2
2.4
2.5
8.8
4.8
a) Calculate the 20th percentile.
b) Calculate the 40th perc