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
STAT 2606 Fall 2015 Assignment #5 (Solution)
Total marks 42
INSTRUCTIONS:
Last Name First Name Student # -Lab group:
PART A: Minitab Questions
1. Hypothesis testing for when is known
Few years ago we recorded the hourly wages of university professors in C
PRACTICE EXERCISES WEEK 5
1. The following table is a partial probability distribution for a company's projected
profits (x = profit in $1000s) for the first year of operation (the negative value denotes
a loss).
100
0.10
x
P(X = x)
0
0.20
50
0.30
100
0.2
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
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
Methods for Describing
Sets of Data
Review
Outlier, Relative Frequency Histogram
Explain Numerical Data Properties
Describe Summary Measures
Central Tendency: Mean, Median, Mode
Learning Objectives
1.
2.
3.
Describe Summary Measures
12 September, 2013
Chapter 2
STAT 2606
CHAPTER 2
DESCRIPTIVE STATISTICS
After measurements are collected then we should describe them. There are two ways:
Graphically.
Numerically.
Graphically
Each graph should provide with the following information:
W
CHAPTER 3
PROBABILITY
Probability
Probability is used to evaluate the reliability and validity of our inference based on the sample in
reference to the population (which is usually unknown).
Experiment is a process by which measurements are observed. Exam
STAT 2606 Assignment #2
Sections C and D: Due Tuesday, October 13, in class at the end of the
lecture
INSTRUCTIONS:
I. Assignments are to be submitted in-class on the due date and at the end of
the lecture. No late assignments will be accepted without suc
Carleton University
School of Mathematics and Statistics
STAT 2606 Assignment #3 Fall 2015
Section C due Tuesday, November 3 at the end of the class
INSTRUCTIONS:
I. Assignments are to be submitted in-class on the due date and prior to beginning of the le
Statistical Inference
Statistical inference is concerned with making decisions or educated guesses
about parameters, numerical descriptive measures of a population. The parameters are usually unknown. Their unknown values are of interest to us.
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Small Sample Inference
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Small-Sample Statistical Test for the population mean
When n observations in the sample are randomly selected from a normal
population with mean and n is small (n < 30
Statistics 2606 Midterm Examination Fall 2015 SOLUTIONS
PLEASE NOTE: STUDENTS ARE NOT PERMITTED TO POST THIS DOCUMENT ONLINE.
Doing so is a violation of Carleton Universitys Academic Integrity Policy.
Part A Multiple Choice Questions: A C E C E B B D B E
STAT 2606 Assignment #1
Section C: Due Tuesday, September 29, In class at the end of the lecture
INSTRUCTIONS:
I.
Assignments are to be submitted in-class on the due date and at the end of the lecture.
No late
assignments will be accepted without sufficie
Sampling Distribution of a statistic
Parameters
Any numerical descriptive measure of a population is called a parameter.
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For a normally distributed population, the mean and variance,
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
Hypothesis Testing
Similar to a courtroom trial, the jury needs to decide between one of two
possibilities:
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The person is guilty.
The person is innocent.
To begin with, the person is assume
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
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
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 FOR WEEK 12
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 chec
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
STAT2606D
Review
Dec 2015
This is only Part of the review questions. Assignment 4 and 5 are also part of
the review.
PART I: Multiple-choice questions (choose one answer ONLY)
Question 1. Random samples of size 36 each are taken from a large population w
STAT 2606: Solutions to Assignment 1
OUT OF 55
PART A
1(A)
The population is all flights from Waterloo, Ontario to Detroit, Michigan during 2010. [1]
The unit is a particular flight from Waterloo, Ontario to Detroit, Michigan during 2010. [1]
1(B)
The var
1. D) The one based on 20 000 is the closer to the true value because according to
the law of large number as states, as the number of an experiment approach infinity
the relative frequency of an outcome will approach to the actual probability of the
outc
1.
D) The one based on 20 000 is the closer to the true value because according to the
law of large number as states, as the number of an experiment approach infinity the
relative frequency of an outcome will approach to the actual probability of the
outc