Big D Incorporated is nearing completion of its portfolio of recommendations for the outdoor sporting goods company. Clearly state your variables that you would utilize in your particular path that you recommend. Utilizing a Regression Model, forecast monthly sales on either the expansion into the new market or if the recommendation is to retrench and not expand. Ensure that you provide adequate justification for your recommendations. The Board of Directors requires your input based upon your previous exercises from Units 1, 2, and 3.
*will privde units 1,2 & 3.
Running head: HYPOTHESIS TESTS
1
HYPOTHESIS TESTS
Colorado Technical University
Luz Sustaita
February 2, 2020
HYPOTHESIS TESTS
HYPOTHESIS TESTS
2
Hypothesis tests are commonly used to compare the results in two different scenarios, or
to compare two samples between them. Individually, chi-square is especially useful when
comparing the mean value of two different sets of data. Briefly, the hypothesis test consists of
defining the two mutually exclusive hypotheses, called null hypothesis and alternative
hypothesis. Once the individual has evaluated the mean and standard deviation of the data, the
analysis can then estimate the t statistic by considering the difference between the two sample
means or the sample mean, and the target mean of the population, divided by the standard
deviation. If the calculated t statistic lies in the critical region, the individual rejects the null
hypothesis, accepting the alternative hypothesis are correct. In contrast, if the calculated t
statistic lies outside of the critical region, he would need to accept the null hypothesis as real, and
hence reject the alternative one (Mendenhall & Sincich, 2016). The critical region is a crucial
element in the evaluation of the results obtained and the final decision made by the hypothesis
test. This critical region is closely linked to the concepts of low
Studies often use statistical tests to verify whether the collected data are useful in proving
their initial hypothesis when trying to analyze a research problem. The selection of the optimal
statistical depends on the exact research question and the chosen experimental design used in the
collection of the data. In this regard, the study needs to adopt the exact statistical test for the type
of research question formulated. For instance, he would use a correlational test to verify whether
there is a direct correlation, either positive or negative, between a dependent and an independent
variable (Schacht, 2018). In contrast, he would use a chi-square test to verify if two or more
variables are dependent or not (Schacht, 2018).
In California case here, there is a positive correlation between the low population and
HYPOTHESIS TESTS
3
a) the people of California are more educated than people of general US. They have
been found to hold more higher education standards than the general USA does. For
that sake, their employability is more.
b) With enhanced employability, the people of California have a better purchasing
power. Thus, a business is more likely to survive in this region. More so;
California has been seen to have a low population. Thus, the resources offered by California are
in abundance thus presenting individuals with the right chances to compete in life, both
educationally, health wise, career wise, among many other elements of life., such that the
absolute value of the correlation coefficient is significantly different from 1, as shown below.
mot educated people. The t would use a correlational test involves the evaluation of the
correlation between the duration of a treatment and its effectiveness.
•
Null hypothesis: The number of incidences depends on the intensity of the implemented
therapy: |r| = 1 and in this case low populations
•
Alternative hypothesis: The number of incidences does not depend on the intensity of the
implemented therapy: |r| ? 1 – employment rate, style of life , number of educated people
Hence, if are no hypothesis testing to verify variables are not correlated, then the
research/study would not observe any significant change when varying the intensity of the
implemented therapy.
On the other hand, the study may want to observe the impact that two or more variables
have on the number of incidences of bad behavior in the child. Using the previous scenario, for
instance, the study would be interested in evaluating whether the number of incidences depends
on the gender and age of the child. In this case, the study could opt for a chi-square independent
HYPOTHESIS TESTS
4
test, in which he evaluates the difference obtained between the observed number of incidences
according to a predefined model and the actual incidences (Schacht, 2018).
The null hypothesis established in such test states that are independent of each other, such
that the age and gender or the child would not influence the number of incidents. In contrast, the
alternative hypothesis establishes that the three variables are not independent, such that the age,
the gender, or both, will impact the number of behavioral incidents establishes that the variables,
as shown below.
•
Null hypothesis: The three variables are independent, such that ?2 ? ?2 critical
•
Alternative hypothesis: The three variables are not independent, such that ?2 > ?2 critical
HYPOTHESIS TESTS
5
Reference
Schacht, S. P. (2018). Social and Behavioral Statistics A User-Friendly Approach (2nd ed.). New
York City, NY(US): Routledge.
BIG D INCORPORATED MARKET ASSESSMENT
COLORADO TECHNICAL UNIVERSITY
LUZ SUSTAITA
JAN. 23, 2020
INTRODUCTION
Population increase Between General US and Chicago Between 1980 to 1990 and 1990 to 2000
16
14
12
10
8
6
4
2
0
US
US female
US males
Chicago
1980-1990
1990-2000
ChicagoFemales
Chicago Males
PROSPECT EARNING AND HOUSING ABILITIES
Percentage increse in Median Household Income and Per
Capita Income between 1990 and 2000
Percentage Increase of House Ownership from
1990 to 2000 between the General US and
California.
71
70
69
68
30
67
20
66
10
65
0
64
-10
US
Owner Occupied Housing
63
US
Median Household Income
Chicago
Per Capita Income
California
Renter Occupied Housing
BUYING POWER AND EMPLOYABILITY
Chart Title
35.00%
30.00%
• California people are more hirable than
the collective residents of US.
25.00%
20.00%
15.00%
10.00%
People of California also have a high
purchasing power than people in
general US.
5.00%
0.00%
College:
College:
College: Graduate College: Some
Associates Degree Bachelor’s Degree
Degree
College, No
Degree
US
California
School: 9th to
11th grade no
diploma
School: Grade K School: High
9
School Graduate
CONCLUSION
? People of California are more educated than people of general US.
? Their employability is better than that of USA.
? People of California have a better purchasing power.
? Thus, a business is more likely to survive in this region.
? California has been seen to have a low population.
? Thus, the resources offered by this county are in abundance.
REFERENCES
? Kurt J. Bauman and Nikki L. Graf. (2003). Educational Attainment: 2000 Census 2000
Brief. Retrieved from: https://www.census.gov/prod/2003pubs/c2kbr-24.pdf
? Marc J. Perry and Paul J. Mackun, Josephine D. Baker, Colleen D. Joyce, Lisa R. Lollock,
and Lucinda S. Pearson. (2001). Population Change and Distribution Census 2000
Brief. Retrieved from: https://www.census.gov/prod/2001pubs/c2kbr01-2.pdf
Statistical Analysis
Colorado Technical University
Luz Sustaita
January 15, 2020
Explain the difference between nominal and ordinal data.
Nominal data
? qualitative
? identifies names
? no assigned order
in relation to
pieces of data or
numbered objects
? calculations
cannot be done
? uses categories
? cannot find mean
or median
Ordinal data
? This data is qualitative
and quantitative
? Data has order.
? There is relation of
numbers .
? There is no meaning
between differences in
data entries
outdoor sporting goods
Qualitative
? Categories of sports
of sports
? what customers
? Brands
Ordinal
• Wants arrange in
order and preference
from the 1 to 5
• Should be arranged
from the list
important to very
important
• Customer needs
• Brand names
Ordinal attribute
? How many people take part in outdoor sports
? Most purchased brand name
?
?
?
?
Adidas
Balenciaga
puma
Asics
Difference between interval and ratio data
Interval Data
?
Ratio Data
Cannot be multiplied or
•
It has an interval scale
divided
•
True zero
?
It is quantitative
•
This data is measured
?
It contains meaningful
differences
?
?
?
on absolute scale
•
It can be used to
This type of data is able to
compare differences ,
interpret scale scores and their
relative, and
differences
magnitudes
In this type of data zero is
•
It gives room for
subjective
multiplication and
There is addition and
division can be
subtraction of constants
performed
Population vs Sample
Differences
Population
• It consist of the
entire group that is
in their natural
environment, the
can be part of the
study or they may
not be
Sample
This is a selected
group of people
taking part in the
study
References
K L I N G B E I L , D . A . , VA N N O R M A N , E . R . , N E L S O N , P . M . , &
B I R R , C . ( 2 0 1 9 ) . I N T E R VA L L I K E L I H O O D R AT I O S :
A P P L I C AT I O N S F O R G AT E D S C R E E N I N G I N
SCHOOLS. JOURNAL OF SCHOOL PSYCHOLOGY , 76, 107123.
W I L L I A M S , P. , H A D L E R , J . , M A R I N G , F. , L E E , R . , R O G E R S , K . ,
S I M O N D S , B . , . . . & L E H M A N , J . ( 2 0 1 7 ) . P O RTA B L E , H I G H A C C U R A C Y, N O N – A B S O R B I N G L A S E R P O W E R
M E A S U R E M E N T AT K I L O W AT T L E V E L S B Y M E A N S O F
R A D I AT I O N P R E S S U R E . O P T I C S E X P R E S S , 2 5 ( 4 ) , 4 3 8 2 – 4 3 9 2 .

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