Treatment of Data and Hypothesis in esearch
During the research, there was data that was collected and having been plotted on the histogram and the appropriate scatter plots, the obtained results gave a descriptive portrayal of the finding from the variables. The histogram and the scatter plot gave the pictorial correlation between the time spent and the frequency of the attendance of the gym session with the audio and visual aids and on the other hand without the aids. The descriptive approach enabled the clear display of the findings such that the correlations were seen clearly hence giving a descriptive statistics at the end of the collection of the data. This descriptive data hence has the potential of giving the researcher easy time in explaining the correlation between the variables involved. The descriptive data also gives the researcher the basic information about the variables that are in a dataset for easy…...

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References

Lund Research Ltd., (2013). Hypothesis Testing. Retrieved May 12, 2015 from  https://statistics.laerd.com/statistical-guides/hypothesis-testing-3.php 

The Regents of the University of Michigan, (2013). Descriptive Statistics. Retrieved May 12, 2015 from  http://www.researchconnections.org/childcare/datamethods/descriptivestats.jsp 

William M.K., (2006). Inferential Statistics. Retrieved May 12, 2015 from  http://www.socialresearchmethods.net/kb/statinf.php

WidgeCorp
A null hypothesis is what is being tested. Essentially, when one runs a statistical test, the objective of the test is to prove the null hypothesis. If the null hypothesis is not proved, then the alternative hypothesis is proved. A good example of this would be trying to test drinking water from a well to prove that it is safe. Let's say that the cutoff for safety is 100 parts per million of a specific element. We cannot tell by looking at it whether or not the water is safe, so we must test it. The null hypothesis is that the water is safe; in other words the null hypothesis is that the water will have under 100 ppm of the element. We run the test on the water and it shows 140 ppm.

This means that the null hypothesis was not proven -- the 140 ppm is higher than 100pm…...

Unit 3

Question

What types of research question(s) can best be addressed through the use of case studies? What are the advantages and disadvantages of the case study approach?

The case study approach is favored in many research studies in the social sciences, particularly sociology and anthropology. Case studies are useful in examining questions about a particular social group, and also explain phenomena with multiple causes, such as 'juvenile delinquency.' Finding ways to treat this sociological problem requires viewing particular types of juvenile delinquency in a sociological context, examining familial and social data as it relates to the behavior, and assessing how, for example, urban delinquency is different from 'small town' delinquency or how delinquency is practiced or viewed differently by various ethnic, racial, and religious subgroups. The question 'do female gang members in urban locations exhibit less violent criminal behavior than their male counterparts' might be a useful case study subject of…...

Nhst
Compare and Contrast Null Hypothesis Significance Testing (NHST)

The most commonly used statistical technique for testing the impact of the factor being discussed on observations is Null Hypothesis Significance Testing (NHST). Consequently, NHST is the famous approach to inferential statistics, especially when conducting quantitative research. Despite being the dominant approach, NHST has also become increasingly controversial given the belief by a considerable number of people that it is a flawed statistical method. The controversy and consideration of Null Hypothesis Significance Testing as a flawed statistical approach has contributed to the development of alternatives whose proponents consider more beneficial or advantageous unlike NHST. However, an understanding of Null Hypothesis Significance Testing requires correct interpretation of p values.

Meaning of p = .05

P value is commonly used across statistical approaches including regression analysis and t-tests because it determines the statistical importance or significance in testing a hypothesis. According to Frost (2014), p values…...

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References

Carver, R.P. (1978). The Case against Statistical Significance Testing. Retrieved November 30, 2015, from  http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.120.780&rep=rep1&type=pdf 

Frost, J. (2014, April 17). How to Correctly Interpret P values. Retrieved November 30, 2015, from  http://blog.minitab.com/blog/adventures-in-statistics/how-to-correctly-interpret-p-values 

Gliner, J.A., Leech, N.L. & Morgan, G.A. (2002). Problems With Null Hypothesis Significance Testing (NHST): What Do the Textbooks Say? The Journal of Experimental Education, 71(7), 83-92.

Levine et al. (2008). A Critical Assessment of Null Hypothesis Significance Testing in Quantitative Communication Research. Human Communication Research, 34, 171-187.

If they can bench-press heavy weights, they may emphasize athletics at the expense of academics, in terms of how they prioritize their time. However, it is equally possible that in some schools, high-achieving students also use athletics as a way of bolstering their college resume. Factors such as the school, the degree to which athletics makes demands upon student athletes within the particular environment, and the intelligence of the players may indicate there is no correlation.
Daily air temperature & the average weight of clothing worn

H1: There is a negative correlation between temperature and weight of clothing -- in other words, greater the air temperature, the lighter the clothing.

H0: There is no correlation between temperature and weight of clothing.

Estimate: Negative correlation -1

Analysis: The research hypothesis is likely to be proven, with only small variations for such factors as rain and humidity.

orks Cited

Shuttleworth, Martyn. Null hypothesis. Experiment Resources.com. 2008.

September 15, 2009…...

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Works Cited

Shuttleworth, Martyn. Null hypothesis. Experiment Resources.com. 2008.

September 15, 2009 at  http://www.experiment-resources.com/null-hypothesis.html

Transient Vibrations and Shock Loads in Spacecraft Components
Increasing performance, as well as the goals of reducing costs, have been the major factors affecting the design of the present and future spacecraft launching system. However, the level of vibration is currently affecting the design process, and launch phase, which may lead to a satellite failure. While it is possible to design the spacecraft to withstand the loads, it is still critical to add a substantial mass to the loads in order to enhance their launching survivability for the satellite operations. However, this option increases the costs of operations as well as reducing the mass margin needed to launch the additional payload. Moreover, on-orbit vibrations can induce spacecraft disturbances leading to negative effects on sensitive payloads' performances. (Denoyer, & Johnson, 2001). Space manipulators have also been identified as the complex systems composing of robotic arms and accommodating the orbiting platform. The…...

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Reference

Denoyer, K. K., & Johnson, C. (2001). Recent Achievements in Vibration Isolation Systems for Space Launch and On-Orbit Applications. American Institute of Aeronautics and Astronautics, Inc.,, 1-11.

Banerjee, A., Chitnis, U. B., Jadhav, S.L., Bhawalkar, J. S., & Chaudhury, S. (2009). Hypothesis testing, type I and type II errors. Ind Psychiatry J. 18(2), 127 -- 131.

Sabatini, M., Gasbarri, P., Monti, R., & Palmerini, G. B. (2011). Vibration control of a flexible space manipulator during on orbit operations. Act a Astronautica, 73, 109-121.

Run a chi-square test for goodness of fit on the variable "Year," testing whether there are equal numbers of STA 250 students in all the represented class years. Copy and paste your output to a Word document and type your answers to the following questions below:
Chi-Square Test

Frequencies

Observed N

Expected N

Residual

Freshman

Sophomore

Junior

Senior

Total

Test Statistics

Chi-Square

df

Asymp. Sig.

0 cells (0.0%) have expected frequencies less than 5. The minimum expected cell frequency is 13.8.

How many students would we expect to see in each of the represented class years if the null hypothesis is true?

How many students do we actually see in each class year? Freshman: 2, Sophomore: 23, Junior: 20, Senior

Is there a statistically significant difference between the distribution of students in the sample and the null hypothesis that there are equal numbers of STA 250 students in each of the represented class years? Write a sentence using the proper format.

The difference is statistically significant because p <…...

carcinoid is no longer rare as previously deemed, but rather is accidentally missed or not analyzed in the course of removing the appendix, this has a major prevalence than most current proportion of reported diagnoses.
Carcinoid tumors are relatively unusual, malignant tumors, typically of the digestive track and/or lung. They grow and develop slowly and as a result have a very minimal probability of disseminating across the body. emarkably, these tumors are abnormal in the sense that they generate hormones, which if let into the bloodstream can cause symptoms such as flushing of the face and/or chest wheezing (Hodgson, 1992). Every so often, owing to the fact that symptoms might be minimal or even lacking, the diagnosis made for carcinoid tumors is usually unplanned, similar to the instances of an appendectomy. The treatment options for carcinoid tumors include radiotherapy and chemotherapy. Surgery is also a treatment option if the tumor…...

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References

Maggard, M. A., O'Connell, J. B., & Ko, C. Y. (2004). Updated population-based review of carcinoid tumors. Annals of surgery, 240(1), 117-122.

Hodgson H. J. (1992). Carcinoid tumors and the carcinoid syndrome. In: Bonchier IA, Allan RN, Hodgson HJ, et al., eds. Gastroenterology: Clinical Science and Practice. London: WB Sanders, 643 -- 658.

Statistical Terms
The author of this report has been asked to answer three broad questions about certain statistical terms and concepts. The first one of those will be standard deviation. The second of the three will be hypothesis testing. The final question will center on standard error and what it means. While statistics may be daunting and intimidating, the concepts and terms used in statistics parlance are not hard to understand or comprehend so long as they are explained and quantified carefully.

The first overall question is what precisely standard deviation happens to be. To put it simply, standard deviation is how dispersed a set of numbers are. For example, the numbers 1, 2 and 3 are very close together so the standard deviation value would be rather small. However, the numbers 1, 1000 and 1,000,000 would have a very large standard deviation because the overall range of the numbers is much…...

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References

Investopedia. (2007). Null Hypothesis Definition | Investopedia. Investopedia. Retrieved 4 July 2015, from  http://www.investopedia.com/terms/n/null_hypothesis.asp 

Investopedia. (2010). Standard Error Definition | Investopedia. Investopedia. Retrieved 4 July 2015, from  http://www.investopedia.com/terms/s/standard-error.asp 

Math Is Fun. (2015). Standard Deviation and Variance. Mathsisfun.com. Retrieved 4 July 2015, from  http://www.mathsisfun.com/data/standard-deviation.html 

Stat Trek. (2015). Alternative Hypothesis: Definition. Stattrek.com. Retrieved 4 July 2015, from  http://stattrek.com/statistics/dictionary.aspx?definition=alternative_hypothesis

To test whether the research results are statistically significant an appropriate test of statistical significance should be run. A chi-square "goodness-of-fit test is used to determine whether a set of proportions have specified numerical values" (Hypothesis testing, 2009, Quick MBA). However, in this specific instance, since it is likely that multiple batch tests for defects will be run, an ANOVA test would be more appropriate: "The primary purpose of ANOVA is to test for differences between multiple means. Whereas the t-test can be used to compare two means, ANOVA is needed to compare three or more means. If multiple t-tests were applied, the probability of a TYPE I error (rejecting a true null hypothesis) increases as the number of comparisons increases" (Hypothesis testing, 2009, Quick MBA). A one-way ANOVA examines whether multiple means differ. "ANOVA calculates the ratio of the variation between groups to the variation within groups" (Hypothesis testing,…...

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References

Hypothesis testing. (2009). Quick MBA. Retrieved December 9, 2009 at  http://www.quickmba.com/marketing/research/ 

Lane, David M. (2009). Null hypothesis. Hyperstat: Online contents.

Retrieved December 9, 2009 athttp://davidmlane.com/hyperstat/A29337.html

Efficient Market Hypothesis
As previously discussed, the weak form efficiency suggests that share prices should follow a random walk, in that each change in share price is unpredictable based on past information. Formally, this is expressed in the following relationship:

where the variables are independent and identically distributed random variables representing equity prices at times 1,2,3…,k. So X is the equity price, the equity price at a point in time n and the change in equity price at any given time is not explained by the past equity price.

The augmented Dickey-Fuller test considers the following model:

where p is the lag order of the process which can be determined by the examination of autocorrelation and autocorrelation plots, and are the factors determined by the regression. The unit root test has the null hypothesis, and the rejection of the null hypothesis implies that the time series is stationary. The variable y refers to the…...

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References

Chen, J. (2008). Variance ratio tests of random walk hypothesis of the euro exchange rate. International Business & Economics Research Journal. Vol. 7 (12) 97-105.

Jamaani, F. & Roca, E. (2015). Are the regional Gulf stock markets weak-form efficient as single stock markets and as a regional stock market? Research in International Business & Finance. Vol. 33 (2015) 221-246.

Wright, J. (2000). Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics. Vol. 18 (2000) 1-9.

23343849
73

0.35009171

35-54

88.40378549

82

0.46387684

55+

81.36277603

93

1.66445872

2 = 11.39

This value does exceed the critical ?2 value for df = 2 at ? = 0.05. Therefore, we can assume that one of the observed values is significantly different from the expected value for that group. Without post-hoc pairwise tests it is impossible to say exactly which group is different. We can make an educated guess, however, that the proportion of 55+ shoppers in store a is statistically different from what would be expected by chance.

3. Collapse the response categories in the following table so that it meets the assumption of the Chi-square test, then perform the test.

Ownership (Collapsed)

Education

Owners

Non-owners

Some High School or Below

5

17

High School graduate

30

25

22

26

Post-Baccalaureate

5

7

Total

62

75

2 = 6.49. This does not exceed the critical ?2 value for df = 3, so we cannot assume that there is any significant difference between the observed counts of home ownership by educational level and those expected by chance.

4. A ?2 test to…...

Technical Analysis in the Implication of Efficient Market Hypothesis on Silver Market
The thesis is for the study of simple commonly used technical trading rules, which are applied on silver market. It covers years 1989 to 2005. A famous study carried out by Lakonishok, Lebaon and in year, 1992 has clearly shown that technical analysis can lead to abnormal prices when compared with buy-and-hold strategy. Other studies have been carried out and found out that technical trading rules cannot over-rule passive investment management strategy. The study uses Brock et al.'s methodology. Several trading rules are discussed (Dawson & Steeley 2003).

LITEATUE IVIEW

In financial theory, efficiency of financial silver market is highly disputed. This has led to many attempts to explain efficiency of silver markets. Eugene.F. Fama formulated the most famous definition in 1970 referred to as the, Efficient Silver market Hypothesis (EHM). The basis of the hypothesis is that a security price…...

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References

Alexander, S.S. (1964) 'Price Movements in Speculative Markets: Trends or Random Walks'. Industrial management Review 5 (2), 25-46

Brock, W., Lakonishok, J., & LeBaron, B. (1992) 'Simple Technical Trading Rules and the Stochastic Properties of Stock Returns'. Journal of finance 4, (5), 1731-1764

Chang, P.H., & Osler, C.L. (1999) 'Methodical Madness: Technical Analysis and the Irrationality of Exchange Rate Forecasts'. Economic Journal 109 (458), 636-661

Dawson, E.R., & Steeley, J. (2003) 'On the Existence of Visual Technical Patterns in the Uk Stock Market'. Journal of Business Finance and Accounting 30 (1-2), 263-293

Data AnalysisTo analyze this data, one must identify the variables and their types. The variables in this dataset are: Participant: Categorical (1 = yes, 0 = no) Extra-Curricular Involvement: Categorical (1 = yes, 0 = no) Residence: Categorical (On campus, Off campus, Parents) Motivation: Numerical (1-10) Life Satisfaction: Numerical (1-10) Exam1: Numerical (0-100) Exam2: Numerical (0-100) Exam3: Numerical (0-100)One can analyze this data using descriptive statistics and data visualization techniques to understand the relationships between variables. Here are some possible analyses that one can perform:1. Descriptive statistics for each variable: Participant: 8 participants (53.3%) are not involved in the program, and 7 participants (46.7%) are involved. Extra-Curricular Involvement: 7 participants (46.7%) are involved in extra-curricular activities, and 8 participants (53.3%) are not involved. Residence: 5 participants (33.3%) live on campus, 4 participants (26.7%) live off campus, and 6 participants (40%) live with their parents. Motivation: The mean motivation score is…...

PAT 1. An opinion poll asks a random sample of 100 college juniors how they view their job prospects once they graduate. Out of the 100 students 53 said Excellent. Find a 95% confidence interval to estimate the proportion of college juniors who think their job prospects are excellent. Assume large samples.The random sample is equivalent to 100 college juniorsFrom this sample, 53 of them considered their job prospects to be excellent, which is equivalent to 0.53.A 95% confidence interval implies that in the event that 100 different kinds of samples are taken into consideration and a 95% confidence interval is calculated for every sample, then roughly 95 out of the 100 confidence intervals will have the true mean value, which is To construct a 95% confidence interval for a population, mean , the correct critical value of z* (Sprinthall, 2003) is P (-1.96 < Z < 1.96) = 0.95The…...

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ReferencesSeber, G. A. (2013). Statistical models for proportions and probabilities. New York: Springer.Sprinthall, R. C. (2003). Basic statistical analysis. Allyn & Bacon.

**Hypothesis 1:** Learners who do not read regularly will better their reading skills than those who don't read fluently. **Hypothesis 1 Result:** Research shows that learners who do not read regularly indeed improve their reading skills at a faster rate compared to those who do not read fluently.
**Hypothesis 2:** Learners who do not read regularly are more likely to better their reading skills than those who don't read fluently. **Hypothesis 2 Result:** The data analysis indicates that learners who do not read regularly have a higher likelihood of improving their reading skills compared to those who don't read fluently.
**H0 (Null Hypothesis):** If....

Statement1: Children who exercise regularly will better their physical form than those who don't exercise. Hypothesis: Children who exercise regularly will show significant improvement in physical form compared to children who do not exercise regularly.
Statement2: Children who exercise regularly are more likely to better their physical form than those who don't exercise. Hypothesis: Children who exercise regularly have a higher likelihood of improving their physical form compared to children who do not exercise regularly.
H0 (null hypothesis): If Children exercise regularly, it has no effect on their physical form as compared to those who don't exercise. H1 (alternative hypothesis): If Children exercise regularly, it....

Statement 1: Hypothesis: Impact of agriculture on food insecurity and nutrition through community gardens using open spaces will have a better impact on urban agriculture to households than on food security and nutrition.
Statement 2: Hypothesis: Impact of agriculture on food insecurity and nutrition through community gardens using open spaces are more likely to have a better impact on urban agriculture to households than on food security and nutrition.
Null Hypothesis: H0 (null hypothesis) - If the impact of agriculture on food insecurity and nutrition through community gardens using open spaces has no effect on the impact of urban agriculture to households compared....

Riya who does yoga asana daily will better her physical fitness is much better than those who does not do yoga. H0 (null hypothesis) - If Riya does yoga asana daily, it has no effect on her physical fitness is much better than as compared to those who does not do yoga. H1 (alternative hypothesis) - If Riya does yoga asana daily, it has an unknown effect on her physical fitness is much better than as compared to those who does not do yoga.

Research studies have shown that regular practice of yoga can lead to improvements in physical fitness. Yoga helps....