TwoSample Test Review
Is the question about means or proportions?
Are the samples paired or not?
Is the question about variability?
For the following problems set up the hypotheses, write the test statistic, and state the assumptions.
1. The following da
TwoSample Test Review
For the following problems set up the hypotheses, write the test statistics with its formula, state the
critical value decision rule, state the assumptions.
1. The following data represent samples of 10 books each of two production
BUSINESS STATISTICS
MGT 216
Spring 2013
The corequisite for this class is College Algebra, if you have not completed or are not
currently enrolled in College Algebra you should not be in this class. This class is a pre or corequisite for many College of
Grading Rubric (With Notes) for Your Memo
When I grade your memos this is what I will look for.
In the memo: (2 points)
I will look for proper memo format including initialing your name on the from line with a
pen.
An introductory paragraph including:
o
o
Review for Test 2
1. Only 30% of all new medicines are profitable.
company developed 10 new medicines last year.
a) How many of the 10 new medicines
eventually become profitable?
A leading drug
would
you
expect
to
b) Calculate the variance for the number
Lesson 17
ANOVA
Instead of comparing means between 2 groups we often need
to compare the _ among _ _
_ groups.
The parametric test to do this is called
_ _ _ (ANOVA).
Definitions:
_ or _ variable: The
quantitative variable you are measuring or observing.
Lesson 16
2 Proportion test &
ChiSquare Test of Independence
ztest for comparing 2 proportions:
The test statistic for comparing proportions of two independent
samples is a 2proportion z test.
For the sample size to be large enough to use this approxim
Lesson 15
Paired ttest
If the two sets of measurements are _ a 2sample (independent) ttest is not appropriate.
Two sets of measurements are related if:

items or individuals are _ or
_ according to some
characteristic(s),

2 measurements are taken on
Lesson 13
One Sample Tests
The pvalue
pvalue: The _ of obtaining a value for the _
_ equal to or more _ than the result
obtained given _ _ _.
If the p value is small:
If the p value is large:
When performing your analysis on computer always use the pval
Lesson 12
Hypothesis Testing
Hypothesis testing enables us to _ _ about a
_ _ of a _
_ by analyzing differences between the
_ _ and the _
_ _. In the words of John Marden
(Professor of Statistics at University of Illinois at UrbanaChampagne) hypothesis te
Lesson 11
Estimation II and Sample Size
Confidence interval for a proportion:
where X=sample number of successes and n=sample size.
Note: P is the sample proportion of successes (events). We are
estimating , the population proportion (probability) of
succ
Lesson 10
Estimation 1
Inferential Statistics: to use _ results to make
inferences about the _ from which the sample
was drawn. The _ population should be the same
as the _ population!
Estimation
_ _: a single value that estimates a
population parameter,
Lesson 9
Sampling and Sampling Distributions
Why sample?
1. Limitations of _ and _.
2. A sample is more _ than a census.
3. Measurement may be _.
Types of Sampling
Nonprobability Sample
Entities chosen without regard to _ of occurrence
in population.
Of
Lesson 8
The Normal Distribution
Continuous Probability Density Function: A mathematical function
That describes probability for a continuous variable.
Area = _, therefore
Total Area under the curve = _.
Area between two values = probability of an occurre
Lesson 7
Covariance and Poisson
Covariance
The covariance is applied to _ _ by
_ _ . The covariance describes how two
variables vary with respect to each other. If the covariance is
_ both investments vary in the same direction,
that is, as the return goe
Lesson 6
Discrete Probability Functions
A _ Distribution for a discrete _
_ is a _ _ listing of all
possible outcomes and their associated _.
presented as a _, _, or _.
This can be
Probability
distributions represent the entire population.
Characteristics
Lesson 5
More Basic Probability
Note: You will need the Binomial tables for Lesson 6!
A population of 200 TSP stores, a womens casual clothing chain
was crossclassified on the basis of frequency of customer
visits (low, medium, high)and if the store was
Lesson 4
Basic Probability
_ is the likelihood that a particular event
will occur.
We can write this symbolically as _.
_ P(E) _.
There are 3 types of probability:
1.
_ _: The proportion of times
that an event can be theoretically expected to occur based
Lesson 3: Quartiles and Plots
Shape
_ vs. _
mean > median: Positive or Right Skewed
mean median: Symmetry or No Skewness
mean < median: Negative or Left Skewed
Stem and Leaf Display separates data into _
_ (the stem) and
_ _ (leaves). You do not have to u
Lesson 2
Describing Quantitative Data
n = sample size, N = population size
Measures of _ _
1.A. _ _
population mean
sample mean
(parameter)
(statistic)
advantage: uses _ from all the _
advantage: has interesting _ properties
(Central Limit Theorem)
disadv
Lesson 1: Frequency Tables and Graphs
Qualitative Data
Summary Table or Frequency Table
What is qualitative data?
Examples:
_ _: A list of all mutually exclusive categories
(classes or outcomes) and their frequency of occurrence.
_ _: Percent or proportio
Learning Project #1
I recommend you work on this project with one partner. If you work with a partner, only one
project (with both of your names on it) needs to be turned in per pair.
1.Usingthewebsitehttp:/www.autotrader.com,findasimplerandomsampleof25To
Formulas for Test 2
Discrete Distributions
x = E ( X ) = x i P ( xi )
= ( xi ) P( xi )
2
2
Poisson Distribution
Binomial Distribution
x = E ( X ) = n
2
x = n (1 )
x = n (1 )
Covariance
xy = [ X i E ( X ) ] [Yi E ( Y ) ] P ( X i Yi )
x = E( X ) =
Formulas for Test 1
x=
x
xw =
=
i
n
w x
w
x
i
N
midhinge =
ii
i
InterquartileRange = Q3 Q1
range = x l arg est x smallest
s2 =
( xi x ) 2
s= s =
CV =
n 1
2
(x
i
Q1 + Q3
2
x)2
2
(x
=
i
N
(x
= 2 =
n 1
s
100%
x
CV =
Positioning Formulas for Quartiles
n
Formulas for Final
Positioning Formulas for Quartiles
Probability Formulas
Statistical Independence
Discrete Distributions
Binomial Distribution
Poisson Distribution
Covariance
Portfolio Expected Return
Standard Normal Distribution
Confidence Intervals
Po
Formula Sheet for Test 3
2sample ttest
Ftest or Levenes test for equal variances
Paired ttest
2proportion test
2 test for independence (Chisquare)
Formulas for Final
Positioning Formulas for Quartiles
Probability Formulas
Statistical Independence
Discrete Distributions
Binomial Distribution
Poisson Distribution
Covariance
Portfolio Expected Return
Standard Normal Distribution
Confidence Intervals
Po