Name _ Pd_ Date_ AP Statistics Practice Quiz Chapter 16
1. A biology professor responds to some student questions by email. The
probability model below describes the number of emails that the
professor may receive from students during a day.
Emails receiv
Week 03: Scatterplots, Correlation,
and Linear Regression
Read Chapters 4 and 5.
Weekly Objectives:
After reading the chapters make sure you can:
1. Determine when a scatterplot is an appropriate graph to answer
questions about the relationship between tw
MEAN
Test of Significance/Confidence Interval for Population Mean
Distribution (based on the sample size)
Choose the distribution from drop down box t-distribution (t-test)
Population Information
Enter Test Mean=
85
Sample Size =
Sample Mean =
Sample Stan
Testing Concepts: Correlation and Regression Lines
1. Match one of the five values of correlation to the associated scatterplot.
a. r = -0.99
b. r = 0.92
c. r = 0.10
d. r = -0.85
e. r = 0.72
Scatterplot
Scatterplot
Scatterplot
16
20
20
14
18
18
16
16
12
1
Elementary Statistics
Week 03 Assignment
Assignment Guidelines:
o Your work must be organized neatly and typed.
o Clearly indicate your name and the assignment number in the file name.
o Electronic copies of your work can be submitted as an attachment to
Fred Smith
Elementary Statistics
Week 03 Assignment
Assignment Guidelines:
All bold and underlined statements correspond with Excel output. Data can be in the
Week 03 Excel file.
1. Changing Units How does it affect correlation and the LSR Line?
How does
Symbol
cfw_
Symbol Name
set
Meaning / definition
a collection of elements
Example
A=cfw_3,7,9,14, B=cfw_9,14,28
A B intersection
objects that belong to set A and set B A B = cfw_9,14
A B union
objects that belong to set A or set B
A B subset
subset has le
Comment on the following graphs. What would you conclude from the scatterplot
and correlation? What additional conclusions can be made from the side-by-side
boxplots? Can you find any explanation on the internet? What do you think about the
following anal
Excel command for Binomial Probabilities is =BINOMDIST(x, n , p ,FALSE)
P(x) for B( 4 , 0.50 )
0.0625
0.2500
0.3750
0.2500
0.0625
P(x) for B( 4 , 0.50 )
0.4000
Probability
Enter n and p below.
4
n=
p=
0.5
n
x
4
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Experimental Design
The best way to establish causation is
by a well-designed experiment.
Recall that an experiment deliberately
imposes some treatment on an
individual or subject.
1
Bad Design
Gastric freezing was once a treatment for ulcers.
Patients wo
Gathering Data
To have reliable results you must scientifically
gather the data.
The conclusions that we draw from data analysis
apply only to the data that we examined.
However, we generally want to answer questions
about a larger group of subjects. In o
The Binomial Setting
1
When the same chance process is repeated several times, we are often
interested in whether a particular outcome does or doesnt happen on each
repetition. In some cases, the number of repeated trials is fixed in advance and
we are i
Week 05: Probability Distributions
Read Chapters 10, 12, and 13.
Weekly Objectives:
After reading the chapters make sure you can:
1.
Understand the basic vocabulary of probability models.
2.
Understand and apply the rules of probability:
complement rule
Normal Distribution
The normal distribution is considered the bellshape curve.
Examples of variables that typically follow a
normal distribution:
Standardized test scores
IQ scores
Heights
Weights
Middle values
are more
frequent.
Low and high values
are
Scatterplots, Correlation, and
Linear Regression
How can we explore the association
between two quantitative variables?
Scatterplots
Correlation
1
Explanatory vs Response Variable
Explanatory Variable: A variable which is used in a relationship
to expl
The Least Squares Regression
Line
How can we explore the association
between two quantitative variables
and use it to predict the outcome of a
variable?
1
Finding a Formula to Describe a
Linear Relationship
Suppose that there is a linear association betwe
Residuals, R-squared, Cautions
Facts about Residuals
R-squared; Assessing the fit of the LSR
line using
Some cautions in analyzing associations.
1
What does the residual measure?
Geometrically, the residual is the vertical
distance the plotted point is
Week 01: One Quantitative Variable
Read Chapters 2 and 3.
Weekly Objectives:
After reading the chapters make sure you can:
1.
Understand and interpret mean, median, and influence of outliers on
these measures.
2.
Understand the concept of variability and
Graphically Displaying Data
Objectives:
1. Distinguish between categorical and quantitative variables
2. Decide which graph is appropriate for a given data set, based on
the nature of the variable:
Bar and/or Pie Charts?
Histograms, Stem-and-Leaf Displays