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significance.
α = 0.01 as stated in the problem
Step 3: Select the test statistic.
Use Z-distribution since σ is known
Step 4: Formulate the decision rule
Reject H0 if |Z| > Zα/2
Step 5: Make a decision and interpret the result.
Because 1.55 does not fall in the rejection region, H0 is not rejected. We conclude that the population mean is not different from 200. So we would report to the vice president of manufacturing that the sample evidence does not show that the production rate at the Scranton Plant has changed from 200 per week.
The Two –Sample Test of Hypothesis
The two- sample hypothesis testing is a statistical analysis used to test if
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In reviewing the many research studies and articles where a hypothesis is used for testing purposes, it was clear that medical studies and clinical research use the words hypothesis and testing more frequently than business and economic sectors. Surely, this could be as a result of my search process, but more likely as a result of the scientific nature of hypothesis testing and its' roots found in true science. Business and other industries have become more scientific with their research approach, which means there will be more evidence of hypothesis testing in business industries like the financial services arena.From the reference article chosen the hypothesis is written very clearly
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o Calculating the Probability of an event
o Events of being mutually exclusive or not
• Normal Distribution
o Finding the area under the curve
o Using Distribution Tables
• Statistical Inference
o Normal Distribution
o Student’s t-distribution
• Hypothesis Testing
o Null Hypothesis
o Alternative Hypothesis
o Type I error (rejecting the null hypothesis when it is true)
o Type II error (accepting the null hypothesis when it is false)
Collectively, Team B has a member of the team in the Tax Industry, two members in Human Resources, a member in the Oil and Gas Industry, and a member in the entertainment industry that uses a lot of technology in his line of work. We all agree that
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Hypothesis:
To statistically evaluate questions, we need to put forward a hypothesis, which is an unproven testable proposition or supposition that tentatively explains certain facts or phenomena. It is a statement of assumptions we have about the nature of populations or relationships. So, Hypothesis is an educated guess based on the material that one has read.
Hypothesis testing involves the careful construction of two statements: the null hypothesis and the alternative hypothesis. To statistically evaluate the truthfulness of a question, one has to develop a null hypothesis (or statistical hypothesis), which will be used to test the proposition or supposition. The null hypothesis
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testing is the use of statistics to determine the probability that a given hypothesis is true. The usual process of hypothesis testing consists of four steps. These steps are as follows:
1. Identify the null hypothesis H0 and the alternate hypothesis HA. A null hypothesis is a hypothesis set up to be nullified or refuted in order to support an alternative hypothesis, which states there is a difference between the procedures. These hypotheses can be stated in the following terms:
a. H0: μ ≥ .10
b. HA: μ < .10
2. When used, the null hypothesis is presumed true until statistical evidence indicates otherwise — that is, when the researcher has a certain degree of confidence, usually 95% to
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? 4. Is there any difference between the strengths of steel wire produced by the XY Company and Bob’s Wire Company? 5. A hospital spokesperson claims that the average daily room charge for a specific procedure is $622. Can we reject this claim?
WHAT IS A HYPOTHESIS?
Hypothesis: A statement about the value of a population parameter developed for the purpose of testing. Examples of hypotheses, or statements, made about a population parameter are: The mean monthly income from all sources for systems analysts is $3,625. Twenty percent of all juvenile offenders ultimately are caught and sentenced to prison.
Hypothesis testing: A procedure, based on sample evidence and probability theory, used to
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process illustrated here, represents psychology as a science and the investigation of inquiries into thought and behavior as a scientific discipline using the scientific method. The scientific method involves a process of asking questions, developing a theory, testing an aspect of that theory based upon a hypothesis, collecting and analyzing data, and drawing a conclusion. Most notably, Wilhelm Wundt, often regarded as the father modern psychology, ushered in a new era of psychology by showing that mental processes could be studied quantitatively (Santrok).
Psychologists as mathematicians
â€œQuantitative research refers to studies in which the findings are mainly the product of statistical
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Xochitl Jacques - Smith
Hypothesis Testing/ Psychological Reasons for Depression
PSY315 Statistical Reasoning
Amber Lupo
July 6, 2015
Psychological Reasons for Depression
The number of people diagnosed with depression will be different because of
either biological or psychological conditions. This hypothesis testing will include a
two-tailed test with the alternative hypothesis testing as there will be a difference in
either biological or psychological
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newspaper. For the operating characteristics, they somewhat prefer the waterfront, like simple décor, prefer the restaurant not too fat from home. And not prefer large variety of Entrees and unusual entrees. In the consumers’ characteristics section, Almost 60% customers have bachelor’s degree and more than half are married with income range from $50,000 to $74,999.
The preliminary analysis give the general idea from the customers, however, the deeper statistical test need to conduct in order to get the deeper understanding with the customers.
Data Screening and Hypothesis Testing
1. How much are potential patrons willing to pay for the entrées? Is the $18 amount from the forecasting model
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Case Executive Summary
Learning Team A
Johnny Reed - Problem Statement & Analysis
Sophia Myron - Hypothesis & Hyperlinks
Ron Hunter - Limitations/Assumptions & Advantages of Statistical Analysis
Justin Hartman - Graph & Workplace Examples
Austin Rentsch - Conclusion & Recommendation
Research and Evaluation II (RES/342)
University of Phoenix
August 10, 2009
.
Problem Statement
In business, the ultimate goal for most companies is to make a profit. In order to achieve profits, companies need
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research from the internet, a statistical hypothesis is a statement about the distribution of the data variable X. Equivalently, a statistical hypothesis specifies a set of possible distributions of X (namely, the set of distributions for which the statement is true). In hypothesis testing, the goal is to see if there is sufficient statistical evidence to reject a presumed null hypothesis in favor of a conjectured alternative hypothesis. The null hypothesis is usually denoted H0 while the alternative hypothesis is usually denoted H1. A hypothesis that specifies a single distribution for X is called simple; a hypothesis that specifies more than one distribution for X is called composite
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research from the internet, a statistical hypothesis is a statement about the distribution of the data variable X. Equivalently, a statistical hypothesis specifies a set of possible distributions of X (namely, the set of distributions for which the statement is true). In hypothesis testing, the goal is to see if there is sufficient statistical evidence to reject a presumed null hypothesis in favor of a conjectured alternative hypothesis. The null hypothesis is usually denoted H0 while the alternative hypothesis is usually denoted H1. A hypothesis that specifies a single distribution for X is called simple; a hypothesis that specifies more than one distribution for X is called composite
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variable, that we should be able to predict the value of the other variable. It’s also important thing to remember about correlations is that whether they are negative or positive, is that they do not determine causation. In this study the variables being measured are or should be quantitative in this example, both student anxiety scores and study hours are quantitative variables meaning both anxiety and hours are represented by numerical values.
In this study we must do hypothesis testing which involves developing two statements the null hypothesis reflects that there will be no observed effect in our study the null hypothesis is what we are overturning by our hypothesis test, and the alternate
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Chapter 4 Questions
11-list the five steps of hypothesis testing and explain the procedure and logic of each.
Step 1: Restate the question as a Research Hypothesis and a Null Hypothesis about the populations (Aron, 2009).
We want to put this into clear terms with our population 1 in the first group stating what our opinion of the research is, why we are performing the research, and what we feel the outcome will be.
We then state a null hypothesis to make clear we understand there is an alternative. That is, our prediction may not be correct, there may be no effect. This is considered population 2.
Step 2: Determine the characteristics of the Comparison Distribution (Aron, 2009).
We
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knowledge of psychological principles to change behavior and influence thought
Theory/Hypothesis
One-tailed vs. two-tailed hypothesis
A one-tailed test looks for an increase or decrease in the parameter whereas a two-tailed test looks for any change in the parameter (which can be any change- increase or decrease)
Two Tailed: If you are using a significance level of 0.05, a two-tailed test allots half of your alpha to testing the statistical significance in one direction and half of your alpha to testing statistical significance in the other direction. This means that .025 is in each tail of the distribution of your test statistic. When using a two-tailed test, regardless of the
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analytical tool for the appropriate situation. Bayes' theorem is more suitable because of the subjective nature of the data. Whenever a given hypothesis is true, hypothesis testing is more effective. In the rental insurance example, hypothesis testing may be used if the probability of different variables is clear. For example, accidents that happened over the long distance range from Salem, OR to San Jose, CA with affecting factors as bad weather conditions, and ratio of morning driving as opposed to night time driving. Night time driving is more dangerous than day time driving. People could fall asleep resulting in having accident. These factors are not clearly described. Therefore, it is
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handle requests. The second step, is determining the statistical tests that will provide accurate data for the report; Chi-squared test, median test, hypothesis test, and a t-test. By completing a cross tabulation, table the results will provide data for relevant testing. Third, determining the statistical significance level by calculating the total number of dealers, means, and standard deviations. Followed by, determining the estimated value, completing the critical value test, and interpret the data to determine the correct hypothesis (Cooper & Schindler, 2011). Since the estimated values are less that the critical values, we accept the null hypothesis.
(Raw data results. , df = 12, P
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problem that can be tested by further investigation.
Can more than one H1 be tested? Yes Can there be an H2? Yes, if the other hypothesis related to the information collected.
3. Can a hypothesis be proven? Why or why not? Yes, a hypothesis can be proven by the data collected during the experiment.
4. Is it sufficient to do a single experiment to test a hypothesis? Why or why not? No, one experiment canâ€™t prove a theory is true.
5. What statistical techniques can be used to add robustness to the data results? This means that if the assumptions are only approximately met, meaning having a bias tending towards 0 as the sample size tends towards infinity.
6. Why is
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Bottling Company Case Study
Vincent Bacon
Dr. Pamela Self
MAT 300 Statistics
December 14, 2013
Bottling Company Case Study
Calculate the mean, median, and standard deviation for ounces in the bottles.
To determine the mean, which is the statistical average of all numbers involved, we will add the number of ounces together and divide by the number of bottles, in this case 30. For the mean we get 446.1 / 30, for a mean of 14.9. The median, however, is the ‘middle’ number of the bottles ounces. Since we have an even number, it will be the average of the two middle numbers, which will give us a better perspective of the average than just the mean will. In this case
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and authentic results can be derived from the study relating to forecasting of the number of candies to be produced (Wenger, 2010).
Project Part 4: Methods, Analysis, and Results
The part four of the project is based on the hypothesis testing in which the significance level is assumed to be 0.05. The critical values are compared with the test statistics so as to determine the null and substantial hypotheses that could used so as to make valid conclusions with valid evidence on the proportions of the different types of candies produced by Masterfoods plant. It can be inferred in this project that the proportion size of the various types of candies is based on real testing of the
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, the researchers tabulated, processed, analyzed and interpret the data obtain.
Statistical treatment
The statistical tools in interpretation of data gathered and testing of the hypothesis of the study included the frequency distribution, mean rating and chi-square test.
Frequency distribution was used in the analysis of the respondent’s profile, while the data gathered in the accomplished questionnaire checklist was categorized, tallied, and tabulated, and as bases for interpretation a scale for mean ratings is used.
Chi- square test was used to determine if there is a significant relationship between the profile of the student and the decrease of CE students population.
Questionnaire
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Tom’s Classic Mustangs
Statistical Analysis of Sales
Leadership and Organizational Behavior
Introduction
We have been asked to analyze nine different variables to determine what if any, relationship they may have against the selling price of used Ford Mustangs at Tom’s Classic Mustangs. We have been provided data for the last 25 Mustangs sold by Tom’s. Please see Appendix A for the raw data.
We will be taking the data for each variable, determine a hypothesis between the variable and the selling price, then test to prove or disprove the hypothesis. A conclusion will be drawn from the test.
Finally, after all the variables have been tested against the selling
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a study's sample?
â€¢ Census
â€¢ Probability sampling
â€¢ Nonprobability sampling
â€¢ Element selection
Want more details? Download now UOP QNT 565 Complete Class
24. The _____ is a parametric test to determine the statistical significance between the sample distribution mean and a population parameter.
â€¢ t-test
â€¢ F statistic
â€¢ Z distribution
â€¢ Z test
25. Jeremy is using an ANOVA to examine the alternative hypothesis that brand loyalty is higher among frequent fliers of Jet Blue than the reported brand loyalty of frequent fliers on United, US Airways, and Delta. If the p value is less than .05 and the F ratio is greater than 1, which of the following interpretations
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) ________ variable at work.
• suppresser
• extraneous
• antecedent
• Component
20. An experimental study is one that
• attempts to reveal why or how one variable produces changes in another
• attempts to capture a population's characteristics by making inferences from a sample's characteristics and testing resulting hypotheses
• involves manipulation of one or more variables to determine the effect on another variable
• discovers answers to the questions who, what, when, where, or how much
To download the Complete Final Exam of QNT/565 click QNT 565 Final Exam
Study Materials
21. The _____ is used to test the statistical significance of the observed association in cross
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gathered information that was useful and could easily be repeated at a later time resulting in a reliable instrument. However, if the Team wished to receive more accurate results they may consider alterations to a few of the questions presented. For example, question five asked the respondent to rate whether his or her carrier offered plans within her or his budget. The question is certainly relative to the research question however, they should consider a follow-up nominal question regarding household income to determine if income levels determine plan satisfaction.
Analysis
The statistical analysis of the data uses calculations designed to accept or reject a stated hypothesis. Team B
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also degrees of freedom. Degrees of freedom have to do with the amount of subjects in your sample. Since this sample has 50 subjects and it is not the entire population, we will be using the degree of freedom of 49.
The significance level is set at .05 meaning that t-testing and then finding the P-Value will be used. Assuming that the means are the same; it will show the odds of choosing a sample that is from the group with the same mean. So, if the null hypothesis is true, the t-test will give me the odds that my mean is a sample with the “true mean” equal to successful applicants. If this value is less than .05, I will reject the null hypothesis.
t=X1-X2- (μ1-μ2)S12n1+S22n2
t=43.68
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be discarded and those which are peripheral should be looked at critically
(Source: http://libguides.library.cqu.edu.au/litreview)
c) Research design: Defines what type of study is being done, types of research questions, hypothesis, variables and any data collection methods. It can be qualitative or quantitative in nature. A research design encompasses the methodology and procedures employed to conduct scientific research. The design of a study defines the study type and sub-type, and, if applicable, data collection methods and a statistical analysis plan. The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent
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analysis measures how strong the relationship is between the two variables.
Week in Relation to the Course
In previous weeks, we used hypothesis testing to draw conclusions about sample data. This week, we use linear regression to make predictions from a sample of data. Additionally, we use hypothesis testing to determine the validity of the regression line in terms of its slope and an ANOVA table to depict key values used to develop the regression equation. Linear regression is a key element of time series analysis presented next week.
Methodology
Regression analysis is used for prediction purposes. A regression model is a statistical model that is used to predict the values of a
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exhaustive discussion, of threats to each validity will be provided. For a comprehensive discussion of the four types of validity, the threats associated with each type of validity, and additional validity issues see Cook and Campbell (1979).
Statistical Conclusion Validity: Unfortunately, without a background in basic statistics, this type of validity is difficult to understand. According to Cook and Campbell (1979), "statistical conclusion validity refers to inferences about whether it is reasonable to presume covariation given a specified alpha level and the obtained variances (p. 41)." Essentially, the question that is being asked is - "Are the variables under study related?" or "Is
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different sets of observation is an important function of statistics. Comparison is necessary to draw conclusions as Professor Boddington rightly points out.” the object of statistics is to enable comparison between past and present results to ascertain the reasons for changes, which have taken place and the effect of such changes in future. So to determine the efficiency of any measure comparison is necessary. Statistical devices like averages, ratios, coefficients etc. are used for the purpose of comparison.
4. Testing hypothesis:
Formulating and testing of hypothesis is an important function of statistics. This helps in developing new theories. So statistics examines the truth and
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display of information can be in a pie chart or simple bar chart of different categories like people who prefer to read electronic books and people who prefer to read hard copy books. Finally, a proper statistical hypothesis testing method can answer the research questions in the questionnaire. In the Barnes & Noble case study, the hypothesis test that proportion of people who prefer to read the electronic copy of books is the same proportion of people who prefer to read hard copy books. The hypothesis test consists of equality of proportions of five populations. The hypothesis test can assist in determining if the emergence of electronic copy of books is reducing the prices of hard bound and
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… it is important to plan the analysis before developing the measurement questions… nominal, ordinal, interval, and ratio scales…each type influence the analysis (statistical choices and hypothesis testing) (Cooper−Schindler, 2006, p. 359).
References
Cooper−Schindler, (2006). Business Research Methods, Ninth Edition. New York: McGraw - Hill Companies.
Ellis, A. (1973). Humanistic psychotherapy: The rational-emotive approach. New York: Julian Press. Retrieved 3/8/11 from http://www.choixdecarriere.com/pdf/5671/28-2010.pdf
Lee, G., Jorge, C., Anita, R., (2008). Emotional intelligence for managing results in a diverse world. Detroit: Davis- Black publishing. Retrieved 3/8/11 from http://books.google.com/books?id=2ZbAz_ZpnskC&printsec=frontcover&dq=Emotional+intelligence+for+managing+results+in+a+diverse+world&hl=en&src=bmrr&ei=1lx2TafuMcrZgAehjcHJBQ&sa=X&oi=book_result&ct=result&resnum=1&ved=0CD0Q6AEwAA#v=onepage&q&f=false
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extremes and create more precise results. Unfortunately this was not done.
When conducting research is it imperative that the information obtained can be used and validated in a way that would allow the researchers to formulate a conclusion based on the original hypothesis, or business issue. Certain steps are necessary when constructing a means to simplify the likelihood of the data being misinterpreted, or miscalculated. However, there are flaws in most research instruments, leaving little room for error when searching to minimize the challenges for testing the reliability and validity of the research question as well as the data. In order for Insuratel to test their hypothesis, they
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below ten and the tolerance statistic is as well above 0.2 for all the independent variables. Hence there is no problem of Collinearity among the variables used in the model and multi regression is appropriate.
Table 5
Testing the hypothesis:
FDI:
The null hypothesis and alternative hypothesis with respect to BSE Sensex and FDI can be stated as follows:
H01: Flow of FDIs in to India and BSE Sensex trend are independent.
Ha1: Flow of FDIs in to India and BSE Sensex trend are dependent.
The p-value related to FDI shown in table 5, is .000 less than 0.05 so null hypotheses H01 is not accepted. Hence it is concluded that Flow of FDIs in to India and BSE Sensex trend
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is best stated in terms of quantitative as well as qualitative probability, where the probability is based on evaluating opinions and information, then estimating this data and finally assigning probability to the outcomes. Therefore, Bayes’ theorem is best used for the purposes of predicting confidence levels for implementing CRM project, predicting the success of an implementation, and or predicting a project’s failure if there is said lapses in project management methodology.
There are other methods also to analyze the market data which can be useful. Hypothesis testing also provides reasonable statistical criteria to evaluate the result of the observation. But it is more suitable for
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two parts. Half of the critical region is to the right and half is to the left. So the critical region contains both the top 5% of the distribution and the bottom 5% of the distribution (since we are testing at the 10% level).
If H0 is true, X ~ Bin(10, 0.5).
If the null hypothesis is true, what is the probability that X is 7 or above?
P(X ≥ 7) = 1 - P(X < 7) = 1 - P(X ≤ 6) = 1 - 0.8281 = 0.1719
Is this in the critical region? No- because the probability that X is at least 7 is not less than 0.05 (5%), which is what we need it to be.
So there is not significant evidence at the 10% level to reject the null hypothesis.
One-tailed tests
In the previous pages, you learned
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might empower them to take ownership of their workplace, and ultimately increase employee retention.
Question 17.6
Which hypothesis-testing procedure would you use in the following situations?
a). A test classifies applicants as accepted or rejected. On the basis of data on 200 applicants, we test the hypothesis that ad placement success is not related to gender.
2- Independent sample Chi-square test, H0: ad placement success is not related to gender. (Independent) Ha: ad placement success is related to gender. â€œThe chi-square test of statistical significance is a series of mathematical formulas that compare the actual observed frequencies of the two variables measured in a sample
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informed decision. The interpretation of data was completed using Bayes’ Theorem as the probability model. Bayes’ theorem shows the relation one conditional probability and its inverse. The key is that the probability of event A given event B depends on the relationship between A and B, and also the probability of A independent of B, and also the probability of B independent of A. Bayes’ theorem is best used to specify how an ideally rational person would respond to confidence levels for purchasing full coverage automobile insurance and predicting the occurrence of an automobile accident.
While there are other effective analytical tools used to derive probability data such as hypothesis testing
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Table of Contents |
Title | Page |
TITLE PAGE | | | i |
APPROVAL SHEET | | | ii |
ABSTRACT | | | iii |
ACKNOWLEDGMENT | | | vi |
TABLE OF CONTENTS | | | viii |
LIST OF TABLES | | | xxiii |
LIST OF FIGURES | | | xxvi |
CHAPTERS | | | |
1 | THE PROBLEM AND ITS BACKGROUND |
| Introduction | 1 |
| Related Literature | 2 |
| Conceptual Framework | 3 |
| Statement of the Problem | 3 |
| Null Hypothesis | 5 |
| Significance of the Study | 6 |
| Scope and Limitation of the Study | 7 |
| Definition of Terms | 8 |
2 | RESEARCH METHODOLOGY | 34 |
| Research Design | 39 |
| Research Locale | 40 |
| The Respondents | 42
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able to show that 75% of participants agreed that biometric technologies would be successful in protecting the rights and confidentiality of patients when healthcare providers were accessing their electronic health (Flores, Win, Susilo, 2010).
Statistical significance of Findings
In research the statistical significance of the research finding is said to be significant when data has been tested and analyzed; and is more than likely true as a result of testing and not that of chance. Surveys and face-to-face interviews were used in the study for adaption of biometric technologies to conduct both qualitative and quantitative research. Based upon the 75% likeliness of adaption
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Tables A1-A4. In addition to the statistical information, the confidence testing results and hypothesis testing can be found in Tables A5-A7.
The students were asked three questions:
* Did you ever copy work off the Internet as your own?
* Did you ever copy answers off another student’s exam?
* Did you ever collaborate with other students on a project that was supposed to be completed individually?
A total of 90 students responded to the questionnaire with the group divided into 48 male and 42 female students. The data showed that 41.11% of the students cheated in some way. The results also concluded that 37.5% of the male students were more likely to collaborate on a
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Introduction 2
GDP/Capita 2
Literacy Rate 5
Life Expectancy 5
Probability 7
Correlation Coefficient 8
Chi Square 12
Hypothesis Test 12
Conclusion 13
Reference…………………………………………………...........14
Appendix 14
Data Analysis of the World Nations Database, 1999
Introduction
The information provides detailed levels of development and statistical data of World Nations in 1999. The data comprises of different variables that is GDP/Capita, literacy rate levels, life expectancy, arable land, urban population, agricultural labour, electricity/capita, built roads/1000 people and Population under 14
We used the available data to interpret
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, and response initiation and set shifting. This research was focused upon achieving two goals. First goal was to improve the understanding on juvenile BPD by focusing upon measures of executive cognition in pediatric BPD 1 and the second goal was to explore â€œthe effects of comorbid diagnoses, psychotropic medications and clinical symptomatology on executive cognitionâ€ (p. 146). Hypothesis of the research was formed based on the evidence that continuity between the juvenile stage and the adult stage of the illness, juvenile BPD participants would exhibit â€œsimilar pattern of cognitive deficit across executive functions, involving deficits in rule attainment, set shifting, spatial
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. Raw Data…………………………………………………………………….35
Abstract
The study aims to determine whether memory plus gold powdered capsule can be an effective memory enhancer for mice to avoid memory lapses. This study sought to answer if there is a significant effect on the mice's memory before and after the intake of the memory plus gold powdered capsule.
The study used experimental method which includes all the preparation of the materials needed, gathering of the materials and testing. There were two (2) different treatments in the experiment and each treatment has three (3) replicates and three (3) samples. To compute for the statistical significance of the study for the data gathered, the
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. Quantitative research has been described as using a 'narrow angle lens' and to rely too heavily on structure and that it is not innovative enough. Some scholars, for instance, argue that the quantitative approach has an over-reliance on hypothesis-testing and statistical analysis of variables. The excessive dependence on complicated statistical tests by quantitative scientists to explain complex social phenomena has concerned many quantitative scholars. In addition to this problem, it is widely believed that a purely statistical approach fails to generate potential hypotheses from the data produced in a study (Silverman, 2000: 7).Finally, even the general public is, at times, highly suspicious of
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software development and computer services (all establishments), by North American Industry Classification System (NAICS), annual, CANSIM (database), Using E-STAT (distributor).
http://estat.statcan.ca/cgi-win/cnsmcgi.exe?
Lang=E&ESTATFile=EStat\English\CII_1_E.htm&RootDir=ESTAT/
(accessed: July 27, 2008)
Hypothesis
In statistical analysis we make a claim, that is, state a hypothesis, collect data, and then use the data to test the claim. We define a statistical hypothesis as “A statement about a population parameter developed for the purpose of testing” (Basic Statistics, 2006, p. 251).
In this sample of Simple Linear Regression, we are showing how that the higher the number
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Decision of Uncertainty Paper
The use of statistical data in decision making can be very helpful. Being able to use the statistics and formulate probabilities to help in the decision making process. There are several different types of statistical processes such as using confidence intervals, calculation of probability (Bayes’ Theorem), and hypothesis testing.
Decision
I am going out of town for vacation for a month and the decision has to be made on whether to purchase a home security system or take the chance of not having any defense. The reason for this is because leaving a house empty for a month is a risk. However, purchasing a home security system is a rather
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problem.
Relationships mentioned in the research question explored that between races and education level, brain health knowledge and races, and brain health knowledge and education level. Since the study is essentially exploratory in nature and no hypothesis was defined, the issue on error probability does not apply even if the researcher proceeded to use a statistical test in analyzing the data collected.
The two results tables, which consist of demographic and health characteristics, are adequately and understandably presented although, the presentation can benefit from improvements to clarity. The author apparently did not rely on these tables to report the study outcomes. Results on the
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20 If we do not reject the null hypothesis, we conclude that:
a. there is enough statistical evidence to infer that the alternative hypothesis is true.
b. the test has made a type II error.
c. there is enough statistical evidence to infer that the null hypothesis is true.
d. there is not enough evidence to infer that the alternative hypothesis is true.
e. it should be rejected
21 Under which of the following circumstances is it impossible to construct a confidence interval for the population mean?
a. A non normal population with a large sample and an unknown population variance.
b. A normal population with a large sample and a known population variance.
c. Non normal population
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.
1. Does the test involve one sample, two samples, or k (more than two) samples?
2. If two samples or k samples are involved, are the individual cases independent or related?
3. Is the measurement scale nominal, ordinal, interval, or ratio?
â€œAfter analyzing the data, Apple has chosen the statistical method for testing the null hypothesis that the means of several populations are equal is analysis of variance (ANOVA). It uses a single-factor, fixed-effects modelâ€ (Cooper & Schindler, p. 477) to compare the effects of the brand (iPhone versus Android) against the variables outlined above.
Conclusion
Apple had been on top within the
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