1. Introduction:
This is the final project for the Data Analysis for Business class. I’ve been learning how to analyze statistics and how those studies will help in predicting and deciding in business cases during this quarter. This project also gives me a chance to use what I have learned in class in real life. My project is about the growth of the number of employments in the fashion designer industry. According to the Bureau of Labor in the United States, a growth of 5% will exist in this industry by 2016. Through this project I want to prove that the prediction of the Bureau of Labor in the United States is true, and reject the hypothesis that the growth of this industry is less than 5%.

2. Body:
You can add a theoretical discussion in your project…this is optional. But, if you want to discuss your study’s goal and basic theoretical truth behind your hypotheses, you are welcome to do that in this section.

3. Hypotheses:
The industry will grow less than 5%.

4. Method:
5.1. Data Collection:
Annual wage of fashion designers by areas, May 2006
Area Name| Employment| Hourly mean wage| Annual mean wage| Los Angeles-Long Beach-Glendale, CA Metropolitan Division| 2500| $34.34 | $71,430 | Los Angeles-Long Beach-Santa Ana, CA| 2920| $33.66 | $70,010 | Riverside-San Bernardino-Ontario, CA| 30| $27.19 | $56,560 | San Francisco-Oakland-Fremont, CA| 240| $36.25 | $75,400 | San Francisco-San Mateo-Redwood City, CA Metropolitan Division| 150| $33.80 | $70,310 | Santa Ana-Anaheim-Irvine, CA Metropolitan Division| 410| $29.49 | $61,350 | Washington-Arlington-Alexandria, DC-VA-MD-WV| 30| $27.07 | $56,300 | Boston-Cambridge-Quincy, MA-NH| 680| $29.80 | $61,990 | Boston-Cambridge-Quincy, MA NECTA Division| 450| $29.61 | $61,600 | Brockton-Bridgewater-Easton, MA NECTA Division| 60| $27.33 | $56,850 | Providence-Fall...

...HypothesisTesting I
Pat Obi
What is a “Hypothesis?”
A statement or claim about the value of a
population parameter: μ, σ2, p
Pat Obi, Purdue University Calumet
2
Decision Rule
1.
x 0
Z
s
n
Compare calculated Z value to Z value from
Table (critical Z value)
Reject H0 if calculated Z value lies in the
rejection/significance region (i.e. region)
ALTERNATIVELY:
2.
Compare p-value to
Reject H0 if p-value <
Pat Obi, Purdue University Calumet
3
Two-Tail Test
Ex: H0: 0 = 50; H1: 0 ≠ 50. Test at α = 0.05
Reject H0 if calculated Z is either less than ZCV
on the left tail or greater than ZCV on the right
0
Rejection region: /2 = 0.025
Rejection region: /2 = 0.025
0
ZCV = -1.96
ZCV = 1.96
Pat Obi, Purdue University Calumet
4
One-Tail Test: Right/Upper Tail
Ex: H0: 0 ≤ 55; H1: 0 > 55. Test at α = 0.05
Reject H0 if calculated Z > Table Z (i.e. Zcv)
0
Rejection region: = 0.05
ZCV = 1.645
Pat Obi, Purdue University Calumet
5
One-Tail Test: Left/Lower Tail
Ex: H0: 0 ≥ 12; H1: 0 < 12. Test at α = 0.05
Reject H0 if calculated Z < Table Z (i.e. Zcv)
0
Rejection region: = 0.05
ZCV = -1.645
Pat Obi, Purdue University Calumet
6
Z Table (critical Z values)
Significance
Level
Zcv
One-Tail Test
Zcv
Two-Tail Test
0.10
1.285
1.645
0.05
1.645
1.960
0.01
2.326
2.576
Pat Obi, Purdue University Calumet
7
Rules Governing the Statement of
Hypothesis
In...

...APP6JMaloney problems 2. 4, 6, 10, 18, 22, 24
2 ) The value of the z score un a hypothesis test is influenced by a variety of factors.
Assuming that all the other variables are held constant, explain how the value
of Z is influenced by each of the following?
Z= M - u / SD
a) Increasing the difference between the sample mean and the original.
The z score represents the distance of each X or score from the mean.
If the distance between the sample mean and the population mean the z score will
increase.
b) Increasing the population standard deviation.
The standard deviation is the factor that is used to divide by in the equation. the bigger the SD,
then the smaller the z score.
c) Increasing the number of scores in the sample.
Should bring the samples mean closer to the population mean so z score will get smaller.
4) If the alpha level is changed from .05 to .01
a) what happens to the boundaries for the critical region?
It reduces the power of the test to prove the hypothesis.
You increase the chance of rejecting a true H
b) what happens to the probability of a type 1 error?
Type 1 error is falsely reporting a hypothesis,
Where you increase the chance that you will reject a true null hypothesis.
6) A researcher is investigating the effectiveness of a new study skills training program for elementary
school childreen. A sample of n=25 third grade children is selected to...

...Name of designer/label
Biography of designer/label
Influences on design
Type of clothing line
PINK TARTAN
Kimberley Newport-Mimran is the president and head designer of Pink Tartan, . The New York Pink Tartan showroom opened in 2004, and the line is now carried at Saks Fifth Avenue, Neiman Marcus, Bloomingdale’s, Holt Renfrew and The Bay as well as specialty stores across North America, Dubai and Seoul.
Newport-Mimran studiedfashion merchandising and manufacturing management eventually moving into a career in the buying office at the Hudson Bay Company, North America’s oldest retailer. Her style philosophy was clear: “simplicity is the secret to elegance.” Newport-Mimran went on to product development and merchandising and specialized in denim and menswear at Club Monaco, where she learned the importance of structure and tailoring. “Execution is key” became her lifelong mantra.
Newport-Mimran later moved to Caban where she further exemplified that sourcing is an art: finding fabric and manufacturing makes the difference in luxury design. There she met and married the CEO, Joe Mimran. Today the pair is viewed as Canadian fashion royalty; Mimran launched the Joe Fresh mass fashion phenomenon after the selling of Club Monaco to Ralph Lauren.
Womenswear
NARCES
(The designer is Nikki irthensohn.)
Nikki is a Canadian of Persian heritage who was born in Austria, and grew up...

...HYPOTHESISTESTING
WHAT IS THIS HYPOTHESIS????
• In simple words it means a mere assumption or supposition to be proved of disproved.
• But, for a researcher it is a formal question that he intends to resolve.
• Example: I assume that 1) under stress and anxiety a person goes into depression.
2) It leads to aggressive behaviour.
Eg. : Students who get better counselling in a university will show a greater increase in creativity than students who were not counselled.
• So, the hypothesis should be capable of being verified and tested.
CHARACTERISTICS
• Should be clear and precise – inferences not reliable
• Capable of being tested
“ A hypothesis is testable if other deductions can be made from it which, in turn can be confirmed or disproved by observation.”
• Should be limited in scope and must be specific
• Should be stated in simple terms -understandable by all concerned.
• Must explain the facts that gave rise to the need for explanation.
BASIC CONCEPTS: NULL & ALTERNATIVE HYPOTHESIS
• If we are to compare two methods A & B and both are equally good, then this assumption is termed as null hypothesis(H0)
• If it is stated that method A is better than method B-alternative hypothesis(Ha)
LEVEL OF SIGNIFICANCE
• A very important concept in the context of hypothesistesting
• It is represented in a % age...

...27 April 2014
Submission date: 9 May 2014
TUTORIAL ON HYPOTHESISTESTING (1)
Basic Concept
1. State the null and alternative hypothesis for each conjecture :
a. A researcher thinks that if expectant mothers use vitamin pills, the birth weight of the babies will increase. The average birth weight of the population is 3.0kg.
b. An engineer hypothesizes that the mean number of defects can be decreased in a manufacturing process of compact disks by using robots instead of humans for certain tasks. The mean number of defective disks per 1000 is 8.
c. A psychologist feels that playing soft music during a test will change the results of the test. The psychologist is not sure whether the grades will be higher or lower. In the past, the mean score was 73.
d. The average time to read a certain passage is 15 minutes. An educator claimed that a course in speed reading will shorten the reading time.
e. A chemist said that he invested an additive which can increase the life of batter. The mean lifetime is 24 months.
f. The mean waiting bus for buses in Klang Valley is 8 minutes. Some roads are restricted to buses only during office hours. A test is performed to see how this has affected the mean waiting time.
2. Determine whether the one-tailed test or two-tailed test is appropriate for the situation given below:
a. Testing whether the newly-purposed highway speed limit increases the number of accidents.
b....

... Are the following assets? If so, whose assets, and why?
(a) Members of the Australian hockey team
(b) A 9-month lease agreement to rent a business office
(c) Expenditure on research and development
(d) An unsigned, documented contractual agreement to build specialised equipment for a client
(e) A building bequeathed to a firm
(f) A 5-year option to acquire property, where the option was purchased by the company a year ago
(a) Human resources arguably meet the definition of assets of the Australian government, or the Australian Institute of Sport (depending upon whether it is accepted that they can be controlled to act in the interests of the reporting entity). However, even if they are regarded as meeting the definition, because of the difficulty of placing a value on them they are not recognised. (A question to debate in class is: If the team is on a losing streak, are the players still assets? As long as they generate future economic benefits, they remain assets whose measurement and probability may not warrant capitalisation as assets.)
(b) Operating lease. For the lessee (tenant), the future benefits that he or she has control over are the benefits under a contract specifying the rights to benefits, e.g. the right to use a motor vehicle for a month. According to AASB 117, there is no intent by the lessor to transfer substantially all ownership benefits and risks to the lessee. Nonetheless, once a contract is in place there is a right to control the inflow...

...What is HypothesisTesting?
A statistical hypothesis is an assumption about a population parameter. This assumption may or may not be true. Hypothesistesting refers to the formal procedures used by statisticians to accept or reject statistical hypotheses.
Statistical Hypotheses
Null hypothesis. The null hypothesis, denoted by H0, is usually the hypothesis that sample observations result purely from chance.
Alternative hypothesis. The alternative hypothesis, denoted by H1 or Ha, is the hypothesis that sample observations are influenced by some non-random cause.
Hypothesis Tests
Statisticians follow a formal process to determine whether to reject a null hypothesis, based on sample data. This process, called hypothesistesting, consists of four steps.
State the hypotheses. This involves stating the null and alternative hypotheses. The hypotheses are stated in such a way that they are mutually exclusive. That is, if one is true, the other must be false.
Formulate an analysis plan. The analysis plan describes how to use sample data to evaluate the null hypothesis. The evaluation often focuses around a single test statistic.
Analyze sample data. Find the value of the test statistic (mean score, proportion, t-score, z-score, etc.) described in the...

...Hypothesistesting I
Kevin Soo
Outline
• • • • Theory and the research process What is a hypothesis? Hypothesistesting Statistical models
Theory and the research process
Theory
• A belief
– Can be true or false – P (belief)
• A proposed/possible explanation for something
– ‘Some students do poorly at statistics because they have less exposure to mathematics’ – ‘Women don’t date me because I’m ugly’ – ‘Manchester United lost the Premier League because they struggled with injury all season’
Theory
• How do we test a belief/theory?
– Collect evidence/data – How probable is the belief/theory to be true in light of the evidence we have?
• P (belief | data)
‘It will rain today’
• P (rain)
– Let’s say 0.5 (50% chance, guessing)
• Test the belief
– Look for rain clouds
• P (rain | no clouds)
– < 0.5 – Decreases our confidence in the belief/theory
‘It will rain today’
• P (rain)
– Let’s say 0.5 (50% chance, guessing)
• Test the belief
– Look for rain clouds
• P (rain | dark clouds)
– > 0.5 – Increases our confidence in the belief/theory
Scientific theories
• Theories predict and explain what will happen under certain conditions
– Observe/test what happens under those conditions to see if theory predicted correctly – Established and accepted theories are those that have evidence supporting them
• Predicted correctly
– Bad theories will have little...