Week 2: Exercises and Homework Problems 1. Of the adult U.S. population‚ 36% has an allergy. A sample of 1200 randomly selected adults resulted in 33.2% reporting an allergy. a. Describe the population. b. What is the sample? c. Describe the variable. d. Identify the statistic and give its value. e. Identify the parameter and give its value. 2. (HWK) A drug manufacturer is interested in the proportion of persons who
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QUIZ 1. She hid candles in her shoes so she could study math at night. Sonya Kovalevsky 2. He was a Greek mathematician whose school got burned down. Pythagorus 3. He was a Greek mathematician known for shouting “Eureka!” in his bathtub. Archimedes 4. Her bedroom wall was covered with calculus notes. Sonya Kovalevsky 5. This German mathematician was a smart child who went to college at age 14. Johann Carl Gauss 6. He was an English mathematician who was born on Christmas Day. Isaac Newton 7. He dropped
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Gender Discrimination: A Statistical Analysis Gender discrimination‚ or sex discrimination‚ may be characterized as the unequal treatment of a person based solely on that person ’s sex. . It is apparent that gender discrimination is pervasive in the modern workplace‚ however‚ its presence and effects are often misrepresented and misunderstood. Statistical testing plays an important role in cases where the existence of discrimination is a disputed issue and has been used extensively to compare expected
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Statistical Reasoning in Everyday Life This chapter taught me the importance of understanding statistical data and how to evaluate it with common sense. Almost everyday we are subjected to statistical data in newspapers and on TV. My usual reaction was to accept those statistics as being valid. Which I think is a fair assessment for most people. However‚ reading this chapter opens my eyes to the fact that statistical data can be very misleading. It shows how data can be skewed to support a certain
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Doing Statistical Analysis Excel provides a large number of statistical functions. These and the tools in the Analysis ToolPak cover most types of statistical analysis that you would need to do in finance and include in your models. Many people look at functions as "black boxes." You input the arguments‚ and the functions provide the answers. In a way this view is true‚ but it is also dangerous - you may use a function or tool incorrectly or misinterpret the results. So take the time to know
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A researcher predicts that watching a film on institutionalization will change students’ attitudes about chronically mentally ill patients. The researcher randomly selects 36 students‚ shows them the film‚ and gives them a questionnaire about their attitudes. The mean score on the questionnaire for these 36 students is 70. The score for people in general on this questionnaire is 75‚ with a standard deviation of 12. Using the five steps of hypothesis testing and the 5% significance level (i.e. alpha
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IT Project Implementation Failures HCS/483 September 19‚ 2012 Dr. Alex Kadrie IT Project Implementation Failures An IT implementation process can be long and tedious‚ or short and simple‚ depending on the size and needs of an organization. While implementing this process it is important to understand the roles and responsibilities of each step. Sometimes when the process is not thought out correctly‚ IT failures happen. IT failures are common reasons that systems do not
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6.2.5 Statistical analysis The values are expressed as mean ± SEM. The statistical analysis was carried out by one-way analysis of variance using SPSS (version 17) statistical analysis program. Duncan’s post hoc multiple comparison tests were used to determine significant differences among groups. P < 0.05 was considered to be significant. 6.3 Results 6.3.1 Liver function tests Liver toxicity markers were assayed to assess hepatic injury. The activities of alkaline phosphatase (ALP)‚ acid phosphatase
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Performance of Safety Incidents Statistical Analysis of Safety Incident Rates Table of Contents Introduction 3 Part I. Graphical Descriptive Statistics 3 Part II. Binomial Probability Distribution 4 Part III. Inferential Statistics 5 Part IV. One Sample Hypothesis T-test 5 Part V. Two Sample Hypothesis T-test 6 Part VI. Paired (matched) Observation – Two Populations Hypothesis 6 Part VII. Linear Regression and Correlation Study 7 Part VIII. ANOVA – One-Way Test of Variance 7 Part
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Project Proposal Statistical Learning and Data Mining Overview: Efficient asset allocation through statistical learning methods and comparison of methods for the creation of an index tracking ETF (Exchange traded fund) Datasets: The datasets are chosen from the website of the book “Statistics and Data Analysis for Financial Engineering” by David Ruppert. The book is mentioned as one of the references for this course. The two data sets chosen are 1. Stock_FX_Bond.csv 2. Stock_FX_Bond_2004_to_2006
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