ANOVA Hypothesis Test
Living near a major city can be a positive aspect of being a homeowner or someone who uses real estate as an investment. Increasing population contributes to land and space diminishing, resulting in high demand for what is available. Industry and markets are in the city, attracting buyers who want to have the convenience of living near commercial properties. The difference in the pay scale between jobs in the city and jobs in the suburbs could contribute to the home prices being less expensive in the suburbs. Many people do not want to live in the middle of the hustle and bustle of the city, causing an increasing number of communities to be built further away from the city. Team C will use an ANOVA hypothesis test to determine whether the price of homes become more expensive towards the center of the city, or less expensive as home buyers look outside the city center. Is the price discrepancy of a home reflected solely on the distance from the city or do other factors (such as buyers, the economy, amenities) contribute to the price of a home? An ANOVA test allows researchers to compare more than two means simultaneously, and trace sources of variation to potential explanatory factors (Doane & Seward, ch. 11, p 439). The team will be reviewing the information presented in the data set and with supporting research will be able to determine if price discrepancies exist. Importance of Research

Nothing affects a home value as much as economy. This particular research problem is highly important for individuals looking to purchase a home to be aware of the price discrepancies. There are two categories of people whom it would be crucial to have a constant update on home prices. Buyers and sellers hold an accountable interest in the real estate field whether the home is being sold through a local real estate agent, or using corporate connections. Individuals who are looking into purchasing a house must...

...Saurabh Sunny Baghmar
MNGT: 6361
Problem Statement: To determine if saving from the total monthly income is gender biased.
Hypothesis: H0: Single Women save equal to single men from their total monthly income. (Null Hypothesis)
H0 = µwomen - µmen = 0
Introduction:
The thought behind this problem statement comes from the report which says that there is a huge difference between the number of single women applying for credit cards and men. There are studies done to project the spending/saving habits of men and women. Research shows that women and men have different interest areas where they like spending money [1]. These areas determine how much they spend. Men spend money mostly on eating out, sports ticket, drinking, cars and boys clubs. Whereas women like to spend money on clothes, jewelry, makeup/spa and other accessories. According to [2], the level of debt for men and women is different. Gender was more influential in predicting financial management practices than was affective credit attitude, with female students employing a greater number of financial practices. Research on credit card behavior [3] among college going men and women states that men apply for more than one credit card whereas women’s hold an average of one credit card during their college education. The identification of gender differences may also indicate the...

...ANOVAHypothesis Testing Paper
RES/342
July 5, 2011
University of Phoenix
ANOVAHypothesis Testing Paper
According to Payscale.com an individual with a high school education entering the work force will earn less than an individual with the same level of education who has worked longer in that particular field (Harrison, 2010). Team A has selected data from the Wages and Wage Earners data set and will be using the analysis of variance, also known as ANOVA, to compare the mean of age groups 18 - 63 which were broken down into four age groups to compare the average salary of each age group and will determine the accuracy of Payscale’s claim. In this paper we discuss our research question and the hypothesis and show how we concluded the selected hypothesis.
Research Question and Hypothesis Statement
Is there a difference in earned wages for workers with a 12th grade education based on the age of the worker? At a five percent level of significance (α), the team’s null hypothesis (H0) is that the mean scores are the same for the four groups 18-25, 26-33, 36-44, and 46-53. The alternate hypothesis (H1) is that at least one mean is different. These hypotheses are simply illustrated as: H0: πgroup 1 = πgroup 2 = πgroup 3 = πgroup 4, H1: At least one mean is different.
Five Steps Hypothesis Testing and...

...One Sample HypothesisTest
Jeremey Yoppini, Mayela Castillo, Kristopher Olstad, Areli Mejia, Heather Smith
RES342
December 21, 2011
Thomas Allen
One Sample HypothesisTest
Earning potential and income of every person is severely different; many factors have a hand in determining the amount of money a person makes and how much his or her earning potential can increase. Some of the factors currently determining the earning potential of people around the United States are; education, marital status, age, union participation, race, age, years of experience, sex, the industry in which the individual works, and the position held by individual. This paper is going to show the correlation between marital status and income, the team has disregarded all other determinants to answer the research question clearly. The research question that the team has developed and the hypothesis was formed from goes as follows; does marital status affect earning potential?
Every decade that passes, it seems as though people are waiting longer to get married. Waiting for job security, completion of college and social norms are just a few factors that influence this trend. This is a big change from 50 years ago, when most people would get married straight out of high school. The fact is being single has some advantages when deciding to start a career, it also affects ones earning potential. Being single allows more...

...Question 4
HypothesisTests of a Single Population
1. Explain carefully the distribution between each of the following pairs of terms:
a) Null and alternative hypotheses
b) Simple and composite hypotheses
c) One-sided and two-sided alternatives
d) Type I and Type II errors
e) Significance level and power
2. During 2000 and 2001 many people in Europe objected to purchasing genetically modified food that was produced by farmers in the United States. The U.S. farmers argued that there was no scientific evidence to conclude that these products were not healthy. The Europeans argued that there still might be a problem with food.
a) State the null and alternative hypotheses from the perspective of the Europeans.
b) State the null and alternative hypotheses from the perspective of the U.S. farmers.
3. Bank cash machine need to be stocked with enough cash to meet demand over an entire weekend. However, the bank will lose out on interest payments on any excess cash stocked into the cash machines. A particular bank believes that the mean withdrawal rate per transaction is normally distributed with a mean of $150 and a standard deviation of $50. Is there any evidence that the bank has got its calculations wrong, if a random sample of 36 customer transactions gives a mean sample of $160? State your null and alternative hypotheses.
4. A random sample is obtained from a population with varianceσ2=625, and the sample...

...Research Question 3 : Is there any significant difference between Buddhist and non-Buddhist in their use of nonviolent strategies to solve problems?
Hypotheses
Null Hypothesis (H₀) : There is no significant difference between Buddhist and non- Buddhist in their use of nonviolent strategies to solve problems
Research Hypothesis (H₁) : There is a significant difference between Buddhist and non- Buddhist in their use of nonviolent strategies to solve problems
Technique used
The technique used when conducting the research question is t-Test of independence.
Reasons for using the technique
The reason why t-Test of independence is used because there are only two group of independent variable, which is Buddhist and non-Buddhist. Besides that, the independent variable is categorical, while the dependent variable is using interval scale.
Another reason for using t-Test of independence is because there are independent groups and the test compares two different groups with each other. Hence, one group cannot be a member of the other group. For this research question, the independent groups are Buddhist and non-Buddhist.
Critical Value
Degree of Freedom
= (N1 - 1) + (N2 - 1)
= (42 – 1) + (18 – 1)
= 41 + 17
= 58
Critical value (use significance level .05) = 2. 00
Calculation
| Buddhist, x | x² | Non-Buddhist, y | y² |
| 4.0 | 16.00 | 3.6 |...

...Elements of a Test of Hypothesis 1. Null Hypothesis (H0 ) - A statement about the values of population parameters which we accept until proven false. 2. Alternative or Research Hypothesis (Ha )- A statement that contradicts the null hypothesis. It represents researcher’s claim about the population parameters. This will be accepted only when data provides suﬃcient evidence to establish its truth. 3. Test Statistic - A sample statistic (often a formula) that is used to decide whether to reject H0 . 4. Rejection Region- It consists of all values of the test statistic for which H0 is rejected. This rejection region is selected in such a way that the probability of rejecting true H0 is equal to α (a small number usually 0.05). The value of α is referred to as the level of signiﬁcance of the test. 5. Assumptions - Statements about the population(s) being sampled. 6. Calculation of the test statistic and conclusion- Reject H0 if the calculated value of the test statistic falls in the rejection region. Otherwise, do not reject H0 . 7. P-value or signiﬁcance probability is deﬁned as proportion of samples that would be unfavourable to H0 (assuming H0 is true) if the observed sample is considered unfavourable to H0 . If the p-value is smaller than α, then reject H0 . Remark: 1. If you ﬁx α = 0.05 for your test, then you are allowed...

...Inflation in the United States is at an all-time high. The recession of the U.S. economy only hinders people more with high gas prices. A one population test using the One Factor ANOVAtest and a five-step hypothesistest can be used to determine if gas prices are equally high in many different states. The samples used to test the hypothesis come from data collected from 30 randomly selected gas stations in six different cities. The hypothesistest and some solutions to consider may have an effect on direct and indirect stakeholders and is very important to the economy as a whole.
Data Points
Utah Virginia California Indiana Florida Virginia
Salt Lake city Wytheville Los Angeles Schererville Milton Richmond
Tina Sheri Jean Jennifer Kim Janet
3.33 3.42 3.85 3.79 3.65 3.37
3.34 3.44 3.83 3.83 3.65 3.59
3.35 3.51 3.79 3.79 3.63 3.41
3.54 3.48 3.79 3.85 3.68 3.49
3.61 3.55 3.89 3.74 3.67 3.46
Background
The purpose of this research is to identify trends and differences in gas prices in various regions of the United States. Gas prices vary across the country, and continually rise and fall, trending as the economy improves and worsens. The increase and decrease of gas prices depend on how well the economy is at the time, and can affect each of its stakeholders differently. The hypothesis is that gas prices,...

...types of peanut butter.
| |Laboratory |
|Peanut Butter |A |B |C |D |
|Brand 1 |16.6 |17.7 |16.0 |16.3 |
|Brand 2 |16.0 |15.5 |15.6 |15.9 |
|Brand 3 |16.4 |16.3 |15.9 |16.2 |
Analyse the data at 5% significance by (a) carrying out a one-way ANOVA to see if there is a difference between the fat content of the three brands; (b) performing a two-way ANOVA to see if there is any difference between the Brands using the laboratories as blocks. (c) Do you think there is any evidence that the results were not reasonably consistent between the four laboratories?
a) One-way ANOVA
| |Laboratory | |
|Peanut Butter |A |B |C |D |Mean |
|Brand 1 | 16.6 |17.7 |16.0 |16.3 |16.65 |
|Brand 2 |16.0 |15.5 |15.6 |15.9 |15.75...