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BUS MGT 2320 Autumn 2016 Technology Assignment
Lecture Instructor:
Mrs. Bonnie Schroeder
Recitation Day/Time:
Tuesday/9:35
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Recitation Week 4 Autumn 2016
Big Ideas
~ Normal:
1. Inference about the population mean, , when is not known and
Use the sample standard deviation, s, to estimate leading to the () = = .
Use the Students t-distribution with n -1 degrees of freedom (r
Forecasting with Time Series - Additional Practice Solutions
(1) Which of the following does not constitute a time series?
A. the number of kilowatts of electricity used by a firm each week last year
B. the daily high temperature in a city for the past mo
Forecasting with Time Series - Additional Practice
(1) Which of the following does not constitute a time series?
A. the number of kilowatts of electricity used by a firm each week last year
B. the daily high temperature in a city for the past month
C. ann
Week 1 Normal and Sampling Distributions Practice
1. For the normal probability distribution, the area to the left of the mean is
A. -0.5
B. 0.5
C. a value between 0 to 1 which depends on the mean
D. 1
E. None of the above answers is correct.
2. Which of
One-sample t Inference [mu] - Additional Practice Problems - Solutions
1. Which of the following statements is false?
a. The t - distribution is symmetric about zero
b. The t - distribution is more spread out than the standard normal distribution
c. As th
Matched Samples [D] - Additional Practice Problems - Solutions
(1) If some natural relationship exists between each pair of observations that provides a logical reason to compare
the first observation of sample 1 with the first observation of sample 2, th
Comparisons [ and p] - Additional Practice Problems
(1) Consider the following hypothesis test:
Ho: 1 2 = 1.7
n1 = 20
X 1= 25.2
H1: 1 2 1.7
n2 = 35
X 2= 20.4
s1= 4
= 0.05
s2= 7
a. What is the appropriate distribution for the test statistic (Z or t)? If t
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Turn off all cell phone and/or other PDA devices and stow them in your book bag. You may not use cell phon
Recitation Practice Problems
One-Way ANOVA Part I
Big Ideas
H0: 1 = 2 = = k
Ha: Not all i are the same, or Ha: At least two i are different
Know all relevant terminology/definitions
o Factor = categorical sorting variable that creates/defines the differe
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Turn off all cell phone and/or other PDA devices and stow them in your book bag. You may not use cel
Print
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First 5 letters of
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OSU dot #
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Turn off all cell phone and/or other PDA devices and stow them in your book bag. You may not use cel
Print
Last name
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MI
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last name
OSU dot #
Failure to follow these instructions will result in automatic point deductions:
Turn off all cell phone and/or other PDA devices and stow them in your book bag. You may not use cell phon
Recitation Week 5 Autumn 2016
Big Idea Using 2 independent samples to compare two population means, 1 and 2, or to compare two population
proportions, p1 and p2.
We continue to require SRS and a Normal distribution for the sample statistic (estimator).
Recitation Practice Problems
One-Way ANOVA Part II
Big Idea If the ANOVA test rejects the null hypothesis of equal means, perform a post hoc analysis of
the differences in means. There are many methods, including:
Fishers Method = no correction: The fami
Recitation Notes and Practice Problems
Two-Way ANOVA
Big Ideas
2 Factors Factor A and Factor B - are categorical sorting variables
o Factor A has a or I levels
o Factor B has b or J levels
Combining each level of Factor A with each level of Factor B creat
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Turn off all cell phone and/or other PDA devices and stow them in your book bag. You may not use cell phon
Recitation Week 9 Autumn 2016
Chi-Square Tests
Big Ideas
This is a class of tests for categorically represented data. The tests are based on a comparison of what is actually
observed in categories to what is theoretically expected to occur in those categ
Week 1 Normal and Sampling Distributions Practice Answer Key
1. B. 0.5
2. D. The standard deviation must be 1
3. A. from - to +
4. Z ~ N(0. 1). P(-1.80 < Z < -1.00) = 0.1228
5. Z ~ N(0,1). P(Z < a) = 0.025. a = -1.96.
6. 0.9876
7.
a) 90.2, 109.8
b) Using
Matched Samples [D] - Additional Practice Problems
(1) If some natural relationship exists between each pair of observations that provides a logical reason to compare the
first observation of sample 1 with the first observation of sample 2, the second obs
One-Sample t Inference [] Additional Practice Problems
1. Which of the following statements is false?
a. The t - distribution is symmetric about zero
b. The t - distribution is more spread out than the standard normal distribution
c. As the degrees of fre
1. Waynes is a Simple Random Sample because in the problem he stated he obtained a random
sample of 25 for each recently graduated MBAs in their specialty. Waynes is an Independent
Sample because he took 25 samples from each Finance and Marketing. The Var
1. Waynes is a Simple Random Sample because in the problem he stated he obtained a random
sample of 25 for each recently graduated MBAs in their specialty.
Waynes is an Independent Sample because he took 25 samples from each Finance and
Marketing.
Standar
1
Midterm 1 Review
Standardizing: Z-scores
2
A z-score measures the number of standard deviations
that a data value is from the mean :
Example:
(x )
z
Suppose X ~ N(100", 5") and Y ~ N(100", 10").
Further suppose that we observe x = 110 and y = 110.
x 11
CASE FORMAT and SUBMISSION INSTRUCTIONS:
Group Case #1 reports and peer evaluations are due at the start of your scheduled lecture on Thursday, 2/9/17.
A file identifying your group number and team mates for Group Case #1 has been posted on Carmen (Group
BUS MGT 2320 Spring 2017 Technology Assignment
Lecture Instructor:
Recitation Day/Time:
Print below
Last name
First name
MI
First 5 letters of
last name
OSU dot #
Instructions:
1. This assignment is individual work (NO collaboration). You may not consult
Week 01 Review of Stats 1430
Learning Objectives
1. Review the normal probability distribution
2. Review sampling distribution for xx and pp
3. Review confidence interval estimates of and p
Normal Probability Distribution
The normal probability distributi
BM2320 Recitation Forecasting with Time Series Part II
Important Ideas
= + + +
1. Autoregression, AR(p):
a. Create predictors of the time series by lagging values of the series
b. Regress the actual time series on the important lagged values of the ser
BM2320 Recitation Forecasting with Time Series Part I
Important Ideas
1. Time Series data versus Cross-sectional data
a. Cross-sectional data are collected at the same, or approximately, the same point in time. The data may
include values of a single vari