Health Survey Florida: Confidence Level at 95% is 1.001191951; Upper Limit is 6.551; Lower Limit is 4.548. The expected value has a 95% chance of being in the confidence range. In the case of the above problem‚ it has a 95% chance of being between 6.551 and 4.548. New York: Confidence Level at 95% is 1.0298559; Upper Limit is 9.0299; Lower Limit is 7.0299. The expected value has a 95% chance of being in the confidence range. In the case of the above problem‚ it has a 95% chance of being between
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98% confidence that the underlying yearly real variance of the portfol Sigma^2= 440 Ho: sigma^2 = 440 H1: sigma^2 not = 440 Statistic 4.9 With 98% confidence Lower limit 3.05348411 Upper limit 24.7249703 With 98% confidence we cannot reject Ho since the statistic is inside the acceptance zone b) Check the same hypothesis with 95% confidence. With 95% confidence
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o equals 1.65: a. Calculate 95 percent and 99 percent confidence intervals for u. b. Using the 95 percent confidence interval‚ can we be 95 percent confident that u is at least 50 pounds? Explain c. Using the 99% confidence interval‚ can we be 99% confident that u is at least 50 pounds? explain d. Based on your answers to parts b and c‚ how convinced are you that the new 30-gallon trash bag is the strongest such bag on the market? (a) (i) 95% confidence interval for μ:n = 40 x-bar =
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Chanelle Henderson Math533 Applied Managerial Statistics Prof. Lisabeth Goble Week 6: Project B: Testing Hypothesis Testing and Confidence Intervals A. The average annual income was less than $50‚000 Null Hypothesis: The average annual income was greater than or equal to $50‚000H₀: µ ≥ 50‚000 Alternate Hypothesis: The average annual income was less than $50‚000. (Claim)Ha: µ <50‚000 Analysis Plan: Significance Level‚ α=0.05.Since the sample size‚ n > 30 I will use z-test for mean to test the
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Project Part B: Hypothesis Testing and Confidence Intervals a. The average (mean) annual income was less than $50‚000 Null Hypothesis: The average annual income was greater than or equal to $50‚000 H₀: µ > 50000 Alternate Hypothesis: The average annual income was less than $50‚000. Ha: µ > 50000 Analysis Plan: Significance Level‚ α=0.05. Since the sample size‚ n > 30 I will use z-test for mean to test the given hypothesis. As the alternative hypothesis is Ha: µ > 50000‚ the given test is
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distribution) • But how close is close enough? Estimation and Confidence • We can ask this question more formally: • (1) How confident can we be that a statistic falls within a certain distance of a parameter • (2) What is the probability that the parameter is within a certain range that includes our sample statistic • This range is known as a confidence interval • This probability is the confidence level Confidence Interval & Probability • A confidence
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SOC 222 -- MEASURING the SOCIAL WORLD Session #6 -- CONFIDENCE INTERVALS Oct 2013 TODAY’S OBJECTIVES 1. Understand what confidence intervals tell us 2. Understand how we get them 3. Know the SPSS procedure for getting confidence intervals Terms to Know Confidence interval Mu (μ) t-curve normal curve RICK’S SITUATION Recap His RQ: Population: Real population mean: Sample: Sample mean: 6 Sampling distribution: 2 Estimated mean
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A2 Practical Investigations Title: The effect of Temperature on the growth of Aspergillus oryzae Develop a Hypothesis This particular investigation is to discover how a range of temperatures effects the growth rate of the fungi Aspergillus oryzae. Most fungi’s tend to survive within the temperature range of 5-35oC‚ with the optimum depending on their normal environmental temperature. The fungi Aspergillus oryzae is heterotrophic which means they taken in their food from dead organic matter and cannot
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the fact that a mistake has been made. It simply means that you have based your findings on incomplete yet representative data. Procedures exist for estimating the maximum amount of sampling error. You will be able to state with a large degree of confidence how much difference there is between your estimate (a statistic) and the true answer (a parameter). Terms Random variable - A characteristic of interest such as the amount spent per year by a Baylor student eating at fast food restaurants
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Math 533 Project Part B In regards to the dataset from AJ Department store‚ your manager has speculated the following: the average (mean) annual income is less than $50‚000‚ the true population proportion of customers who live in an urban area exceeds 40%‚ the average (mean) number of years lived in the current home is less than 13 years‚ the average (mean) credit balance for suburban customers is more than $4300. Part 1. Using the sample data‚ perform
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