STAT 2606 Fall 2015 Assignment #5
Sections C: Due Tuesday, December 3, in class at the end of the lecture
Sections D: Due Friday, December 4, in class at the end of the lecture
INSTRUCTIONS:
I. Assignments are to be submitted in-class on the due date and
Comparing Two Population Proportions
by Using Large, Independent Samples
Select a random sample of size n1 from a population, and let denote the proportion of
units in this sample that fall into the category of interest
Select a random sample of size n2 f
PRACTICE EXERCISES FOR WEEK 7
QUESTION 1
Let X represent the number of snacks your professor eats on a randomly selected day, as described by the
probability table below.
x
0
1
2
P(X = x)
0.10
0.50
0.40
a) Calculate the mean and standard deviation of the
Statistics Assignment #3
Streisanne Suter
100880402
STAT2606B4
Part A
1.a) 4.99444
b) 7+3/2=5
c) These to values are extremely close to one another.
d) mean= 8.1
sd= 7.953
Yes these values are close to 8 because the mean and standard deviation of such dis
Carleton University
School of Mathematics and Statistics
STAT 2606: Business Statistics I - Assignment 4
Sections A and B due Monday, November 16 before 3:00pm
INSTRUCTIONS:
I)
Assignments are to be uploaded to the course website on CULEARN as a single le
Business Statistics I
Discrete Random Variables
Review
1.
Random Variable, Discrete Random Variable.
2.
Mean, Standard Deviation
Learning Objectives
1. Describe the Binomial Distribution and calculate
probabilities for it
2. Compute the Expected Value & V
Business Statistics
The Normal Probability Distribution And Sampling
Distribution
Review
Describe the Normal Random Variables
Calculate Probabilities and Values for Normal Random
Variables
Learning Objectives
Central Limit Theorem.
Approximate the Bin
Business Statistics I
The Normal Probability Distribution
Review
1. Describe the Poisson and Hyper-geometric Distribution
and calculate probabilities for it
2. Compute the Expected Value & Variance of Binomial
Random Variables
3. Check the CDF Table
2
Lea
Business Statistics I
Discrete Random Variables
Review
1.
The Law of Total Probability
2.
Bayes Rule
Learning Objectives
1.
Random Variable, Discrete Random Variable.
2.
Mean, Standard Deviation.
Random Variable
Random Variable
1)
2)
3)
4)
5)
6)
Consider
Business Statistics I
Discrete Random Variables
Review
1. Describe the Binomial Distribution and calculate
probabilities for it
2. Compute the Expected Value & Variance of Binomial
Random Variables
3. Check the Binomial Table
Learning Objectives
1. Descri
Business Statistics I
Confidence Intervals (I)
Review
1.
The Sampling Distribution of the Sample
Proportion
2.
Explain Sampling Distribution
3.
Describe the Relationship between Populations &
Sampling Distributions
4.
Sampling Plans and Experimental Desig
Business Statistics I
Confidence Intervals (II)
Review
State What Is Estimated
Distinguish Point & Interval Estimates
Explain Interval Estimates
Example
Example
Example
Learning Objectives
1.
Compute Confidence Interval Estimates for
Population Mean &
Business Statistics I
Confidence Intervals (III)
Review
1.
Compute Confidence Interval Estimates for
Population Mean & Proportion ( Known)
2.
Find the sample size
3.
Estimating the Difference between two
means ( Known) or two proportions
Learning Objectiv
Business Statistics I
Hypothesis Testing
Review
Solve Hypothesis Testing Problems of Mean Based on a
Single Sample
Learning Objectives
1.
P-value
Observed Significance Levels:
p-Values
p-Value
1.
2.
Probability of Obtaining a Test Statistic More
Extreme
Business Statistics I
Distribution And Sampling Distribution
Review
Central Limit Theorem.
Approximate the Binomial Distribution Using the Normal
Distribution
The Sampling Distribution of the Sample Proportion
Learning Objectives
1.
Explain Sampling Di
Business Statistics I
Statistical Inferences Based on Two
Samples
Review
1. Solve Hypothesis Testing Problems for Two Populations
1) Mean
Learning Objectives
1. Solve Hypothesis Testing Problems for Two Populations
1)
2)
Mean
Proportion
2. Distinguish Ind
Business Statistics I
Hypothesis Testing
Review
1.
Distinguish Types of Hypotheses
2.
Describe Hypothesis Testing Process
3.
Two-Tailed Z Test of Mean ( Known)
Learning Objectives
1.
Solve Hypothesis Testing Problems Based on a Single
Sample
1) One tailed
Business Statistics I
Statistical Inferences Based on Two
Samples
Review
1.
Solve Hypothesis Testing Problems of Proportion Based
on a Single Sample
2.
P-value
Learning Objectives
1. Solve Hypothesis Testing Problems for Two Populations
1) Mean
2)
Test of
Business Statistics I
Hypothesis Testing
Review
1.
Compute Confidence Interval Estimates for Population
Mean ( Unknown)
2.
Estimating the Difference between two means (
Unknown)
Learning Objectives
1. Distinguish Types of Hypotheses
2. Describe Hypothesis
Carleton University
School of Mathematics and Statistics
STAT 2606: Business Statistics I - Assignment 4
Section C due Tuesday, November 17 at 2:25pm.
Section D due Wednesday, November 18 at 2:25pm.
INSTRUCTIONS:
I)
Assignments are to be submitted in-clas
Business Statistics I
Methods for Describing
Sets of Data
Review
1.
2.
Survey Sampling.
Statistical Process Control
Learning Objectives
1.
2.
3.
4.
Describe Qualitative Data Graphically
Describe Numerical Data Graphically
Create & Interpret Graphical Disp
STAT 2606 EXAM REVIEW QUESTIONS
1. Adam takes a random sample of 8 oranges and Eve takes a random sample of 12 apples.
Adam's sample of oranges yields an average weight of 15 ounces with a standard deviation of 4
ounces. Eve's sample of apples yields an a
PRACTICE EXERCISES WEEK 10
1. A university bookstore wishes to estimate the average price of all available
textbooks. Assume that = $32. A random sample of 43 textbooks yields a sample
mean of $172. At the 1% level of significance, is there sufficient evi
PRACTICE EXERCISES WEEK 11
1. A research manager at Coca-Cola claims that the true proportion, p, of cola
drinkers that prefer Coca-Cola over Pepsi is greater than 0.50. In a consumer taste
test, 100 randomly selected people were given blind samples of Co
PRACTICE EXERCISES FOR WEEK 9
QUESTION 1
A store manager wishes to compare the service times of the express checkout with the service times of the
self-serve checkout. Suppose that independent random samples of 121 customers at express and selfserve check
STAT 2606 A AND B: PRACTICE EXERCISES FOR WEEK 1
QUESTION 1
A small class has 6 students. How many different simple random samples of size three can be
drawn from this class?
QUESTION 2
An editor wishes to make a statement about the mean number of errors
STAT 2606 A AND B: PRACTICE EXERCISES FOR WEEK 2
FINAL ANSWERS
QUESTION 1
a) The bar chart should be graphed with five non-adjoining bars of equal width. The first bar
would be up to a height of 73 for Accounting, the second to a height of 52 for Finance,
STAT 2606 A AND B: PRACTICE EXERCISES FOR WEEK 2
QUESTION 1
The student placement office at a university conducted a survey of last years business school
graduates to determine the general areas in which the graduates found jobs. A random sample of
253 gr
PRACTICE EXERCISES WEEK 4
1. In one population, 23% of all people have high blood pressure, 30% are
overweight, and 18% suffer from both conditions. Let H represent the event that a
randomly selected person has high blood pressure, and let W represent the
Percentiles and Quartiles
Patrick J. Farrell (2015)
Percentiles
The pth percentile of a data set is a value such that p% of the
observations in the data set fall below this value.
For example, suppose that a student scores 33 out of 40 on a statistics
mi
Graphical Displays for
Quantitative Data
PART 1
Patrick J. Farrell (2015)
Describing Quantitative Data
The three most common ways to present quantitative data graphically
are with a
histogram
stem-and-leaf plot
dot plot
These graphs provide information r
Graphical Displays for
Quantitative Data
PART 2
Patrick J. Farrell (2015)
Stem-and-Leaf Plots
To generate a stem-and-leaf plot, each data observation is split into a
stem and a leaf.
The leaf is the rightmost digit. The stem consists of all of the remain
Measures of Spread
(Variability)
PART 1
Patrick J. Farrell (2015)
Measures of Spread (Variability)
Range: Difference Between Maximum and Minimum Values
Sample Variance, s2, and Sample Standard Deviation, s
Example
First Weekend Receipts of Movies Earning
A Partition of a Sample Space
A sequence of events B1, B2, , Bn form a partition of a sample
space S if and only if the following two conditions are satisfied:
1. S = B1 B 2 B n , and
2. B i B j = cfw_ for i j .
B1
B2
2015 Wayne Horn (excluding images)