As the sample sizes got larger the percentage bean to level off. As seen in the fourth integer it
starts off in the 17th% then goes to 25th% and then stays in the 25th % for the final variable. In
some cases the integers started out with a large percentag
To me it seems like all the graphs offer the same information to me. None of them stand out to
me. Yes the 250 stand out on the graph. The data on the graph is not spread out. It is either on
the low end of the high end. The mean is on the two graphs were
The histogram gives you more data then the boxplot. The frequency and norm are shown on the
histogram while the box only shows the normal. I feel that the histogram is more informative. It
spreads the information out and allows you see it much easier. It
DescriptiveStatistics
N
Mean
StDev
SEMean
100
50.210
31.138
1.700
95%CIfor
(46.878,53.542)
:meanofInteger
Knownstandarddeviation=17
DescriptiveStatistics
N
Mean
StDev
SEMean
100
50.210
31.138
3.114
95%CIfor
(44.031,56.389)
:meanofInteger
The difference be
Statistic
s
Variab
le
Norma
l
N
*
0
N
5
0
Mean
50.77
01
SE
Mean
0.7364
StDe
v
5.20
73
Minimu
m
37.930
8
Media
n
51.84
27
Q3
54.53
99
Maximu
m
60.095
6
Q1
58.29
75
Media
n
61.84
27
Q3
64.53
99
Maxim
um
70.095
6
Q1
482.9
75
Media
n
518.4
27
Q3
545.3
99
Maxi
Is it better to
Write
Why do you
use C2 or C3
symbolically
think C2 or
to find the
P(x ? n)
C3 better?
value
What is the probability of
C3 based on
a statement error
P(X<N)
C3
the numbers
in exactly 2statements?
being larger.
What is the probability of
a
This is an example of quantitative discrete data. There several high points on the graph over the
data. The result were spread across the board. There was no real surprise to the result gathered
in this research. The students were pretty close to each oth
Histogram of C1
16
14
Frequency
12
10
8
6
4
2
0
0
2
4
6
8
C1
This data set looks like how many times something happens over a period of time. It does look
like the frequency is unpredictable which can be scary. It seems as though as time progresses it can
Heather Bennet
Minitab Assignment 2
Boxplot of C1
17.5
15.0
C1
12.5
10.0
7.5
5.0
Histogram of C1
18
16
14
Frequency
12
10
8
6
4
2
0
6
8
10
12
14
16
18
C1
1) The boxplot lets the person know the averages of the group of numbers. The histogram tells the
per
Activity 1.1.3: Persons of Interest
Person of Interest Alex Garcia:
Alex is Annas former husband.
Alex and Anna went through a nasty divorce last year. As soon as the divorce
was finalized, Alex quickly remarried a much younger woman.
Alex and his new wif
Chapter 12
Linear Regression and Correlation
12.1 Linear Regression and Correlation1
12.1.1 Student Learning Outcomes
An outline of what
we're going to be
doing in this chapter!
By the end of this chapter, the student should be able to:
Discuss basic idea
Chapter 4
Discrete Random Variables
4.1 Discrete Random Variables1
4.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to:
Recognize and understand discrete probability distribution functions, in general.
Calculate and i
Chapter 2
Descriptive Statistics
Review the Student
Learning Outcomes for this
chapter; this is an outline of
the material we will study.
2.1 Descriptive Statistics1
2.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to
Chapter 8
Confidence Intervals
Again, a list of what we'll be
covering in this chapter.
8.1 Confidence Intervals1
8.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to:
Calculate and interpret confidence intervals for
Chapter 3
Probability Topics
3.1 Probability Topics1
3.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to:
While this is an introduction
to Probability, this is
generally a new topic for
students in this class; take
yo
Chapter 1
Sampling and Data
1.1 Sampling and Data1
1.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to:
Recognize and differentiate between key terms.
Apply various types of sampling methods to data collection.
Cre
Andee Neuscheler
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Chapter 7
The Central Limit Theorem
7.1 The Central Limit Theorem1
7.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to:
Recognize the Central Limit Theorem problems.
Classify continuous word problems by their distribu
Chapter 5
Continuous Random Variables
1
5.1 Continuous Random Variables
We will omit the
exponential distribution.
5.1.1 Student Learning Outcomes
By the end of this chapter, the student should be able to:
Recognize and understand continuous probability
Andee Neuscheler
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Mat 129-67 - Statistics
Mary Jane Heider
[email protected]
Summer 2016
Genesee Community College
Catalog Description and Student Learning Outcomes . 2
How to Contact Me . 3
Books and Materials. 4
Schedule . 5
Grading .
Andee Neuscheler
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