U4-3
Example
We reasoned that, even if those who drink more
coffee get less sleep, we cannot say that coffee is the
cause. Maybe a subjects high stress level is what
causes him or her to sleep less. We dont know!
Stress level is said to be confounded with
Unit 3 Practice Questions Solutions
1. The six plays that are chosen (in order) are:
14
03
09
01
04
12
Much Ado About Nothing
Taming of the Shrew
Julius Caesar
Merchant of Venice
Midsummer Nights Dream
Romeo & Juliet
2. The four courses that are chosen (i
STAT 1000 Practice Assignment 5 Solutions
1. A statistic is a number that describes a sample, whereas a parameter is a number that
describes an entire population.
(a) $72,240 parameter
$68,179 statistic
19% parameter
110 statistic
(b) 30,000 parameter
37%
U1-3
Some Definitions
A variable is a characteristic or property of an
individual.
Time until a light bulb burns out
Heart Rate of smokers vs. non-smokers
Number of Heads in five tosses of a quarter
Hair Colour
Your Grade in this course
U1-1
U1-4
Som
U2-3
Explanatory and Response Variables
In this second case, one of the variables is an
explanatory variable (which we denote by X) and
the other is a response variable (denoted by Y).
A response variable takes values representing the
outcome of a study,
STAT 1000 Quiz # 2 Solutions
*Note: There are several versions of the quiz (all of them similar). This
is the solution for one of the versions.
1. We would like to determine how a students GPA can be used to predict his or
her final exam score in a statis
Unit 4 Practice Questions Solutions
1. (a) This is a completely randomized design.
(b) The experimental units are the 60 cold sufferers.
(c) There are two factors in this experiment type of beverage and brand of cough
syrup.
(d) Type of beverage has three
Unit 5 Practice Questions
1. Determine whether the values in bold are parameters or statistics:
(a) According to the 2011 Canadian census, the median income of households in Canada
is $72,240. In a random sample of 500 Canadian households, the median inco
STAT 1000 Quiz # 1 Solutions
*Note: There are several versions of the quiz (all of them are similar). This is
the solution for one of the versions.
1. (a) The National Hockey League consists of 30 teams. The average number of wins last
year for the 23 Ame
Unit 1Examining Distributions
Types of variables.
Displaying distributions with graphs.
STAT1000 - Basic Statistical Analysis I
Describing distributions with numbers.
Fall 2014
What is the study of Statistics?
Statistics provide the tools and ideas for us
Sample Term Test 2A
1. A variable X has a distribution which is described by the density curve shown below:
What proportion of values of X fall between 1 and 6?
(A) 0.550
(B) 0.575
(C) 0.600
(D) 0.625
(E) 0.650
2. Which of the following statements about a
Unit 10 Inference for the mean of a population when is
unknown.
Objectives
Inference for the mean of a population:
The t distributions.
The one-sample t confidence intervals.
Unit 10 Inference for the mean of a population
when is unknown.
The one-sample t
Assignment 1 Due date: September 17 for Class 6
September 18 for Class 3
Question 1:
The following tables give the results for the top three horses in the first three
races at Assiniboia
Assignment 2
Due date: October 1 for class 6
October 2 for class 3
Question 1:
(a) The manager of an ice cream store at Grand Beach would like to study the
relationship between the temperature and th
Unit 5 Density Curves and the Normal Distribution
Unit 5 Density Curves and the Normal Distribution
Density Curves
Density Curves
We have some data and draw histograms and we get a picture of the
distribution.
Returning to our histogram from our barley ex
STAT 1000 Formula Sheet
n
1 X
1. r =
n 1 i=1
xi x
sx
yi y
sy
sy
sx
2. b1 = r
3. b0 = y b1 x
n k
4. P (X = k) =
p (1 p)nk
k
5. z = r
6. p z
p (1 p)
n
r
p (1 p)
n
z
m
2
7. n =
p p
p (1 p )
1
n
X
1
=
(xi x) (yi y)
(n 1)sx sy i=1
Unit 2 Scatterplots, Correlation and Regression
Unit 2 Scatterplots, Correlation and Regression
Termniology
So far, we have been looking at different ways to summarize and depict a
single quantitative variable. We will now begin looking at relationships t
Assignment 6 Solution
Question 1. (a) A 90% confidence interval for the true mean radiation level in the
laboratory is
(b) We only know the value of the sample standard deviation s, so we will use
the t distribution in our inference procedures.
(c) The nu
International College of Manitoba
STAT 1000
Basic Statistical Analysis
Fall 2014
Calendar Description
An introduction to the basic principles of statistics and procedures used for data analysis. Topics
to be covered include: gathering data, displaying and
Question 1:
(a) The total area under a density curve must always be equal to one. The area of a
rectangle is base*height, so we have
area = base*height = (79 - 22)* height = 57* height = 1
height =
(b) Any area under the uniform density curve is another r
Assingmnet 4 answer sheet
1. (a) There is no constant probability of success p. The cars near the front of the line
have a greater chance of getting through the intersection before the next red light than the
cars at the back of the line. Outcomes are als
Unit 6 Randomness and Probability
Unit 6 Randomness and Probability
Variability and Randomness
Probability
Statistics involves the study of variability. But how can we work with
something that involves so much uncertainty?
Roll a die, toss a coin, or buy
Question1:
a)
b)
c)
When the desired margin of error decreases by a factor of k, the required sample
size increasesby a factor of k2. Since we are cutting the margin of error by a
factor of 3, we require 32, or 9 times the original sample size. You can se
STAT 1000 Formula Sheet
n
1 X
1. r =
n 1 i=1
2. b = r
xi x
sx
yi y
sy
sy
sx
3. a = y b
x
n k
4. P (X = k) =
p (1 p)nk
k
5. z = r
6. p z
p (1 p)
n
r
p (1 p)
n
z
m
2
7. n =
p p
p (1 p )
1
n
X
1
=
(xi x) (yi y)
(n 1)sx sy i=1
U8-3
Statistical Inference
We get data from a sample, but we are often not
satisfied with information just about the sample itself.
We would like to use this sample data to infer
something about the population of interest.
Statistical Inference provides m
U11-3
Confidence Interval for a Population Proportion
We take a simple random sample of n individuals and
calculate the proportion that possess some characteristic
of interest. A 100(1 )% confidence interval for a
population proportion p is given as
Ideal
U2-3
Explanatory and Response Variables
In this second case, one of the variables is an
explanatory variable (which we denote by X) and
the other is a response variable (denoted by Y).
A response variable takes values representing the
outcome of a study,