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 = sample mean = 6 Estimated standard error = CONFIDENCE INTERVALS Way for rick to talk about how accurate he
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that the resulting interval will have an acceptable amount of sampling error. To compute the sample size‚ you must know three factors: • The desired confidence level‚ which determines the value of the critical value from the standardized normal distribution • The acceptable sampling error • The standard deviation In some business-to-business relationships that require estimation of important parameters‚ legal contracts specify acceptable levels of sampling error and the confidence level required
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C = S ⋅ N ( d1 ) − X ⋅ e − rt ⋅ N ( d 2 ) σ2 μ 2|1 = μ 2 + ρ ( z1 − μ1 ) σ1 Modeling Financial Markets with 45 40 35 30 25 20 15 10 5 0 120.00% Excel and VBA 100.00% 80.00% 51 60.00% 50.5 40.00% σ = ω ⋅ Ω ⋅ω 2 p 0 0. 02 0. 04 0. 06 0. 08 0. 1 -0 .1 -0 .0 8 -0 .0 6 -0 .0 4 -0 .0 2 Frequency Histogram Bin T 20.00% 50 0.00% 49.5 49 48.5 1 Ben Van Vliet May 9 ‚ 2011 13 25 37 49 61 73 85 97
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QNT 351 Final Exam1) The main purpose of descriptive statistics is to2) The general process of gathering‚ organizing‚ summarizing‚ analyzing‚ and interpreting data is called3) The performance of personal and business investments is measured as a percentage‚ return on investment. What type of variable is return on investment 4) What type of variable is the number of robberies reported in your city5) What level of measurement is the number of auto accidents reported in a given month6) The names of
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discovery phase of the lawsuit‚ when both side submit all of the information they have to each other‚ the insurance company hired an independent CPA firm to calculate the GPF. To determine fraud‚ our group had to find the probability that a standard normal random variable exceeded the GPF samples given to us. We used the entire data set of 3‚005 invoices as the population‚
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VaR and expected shortfall — have addressed longstanding regulatory concerns with traditional VaR. Part I describes the calculation of VaR in its conventional form. For illustrative purposes‚ Part I will describe parametric VaR on a Gaussian distribution. Part II summarizes known weaknesses in VaR‚ from inherent model and estimation risk to VaR’s failure to perform under extreme economic stress and VaR’s failure to satisfy the theoretical constraints on “coherent” measurements of risk. Part
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Text Book Study Guide Part II BMGT452‚ Fall 2011 [pic] Review the scale of the measurement: Nominal‚ Ordinal‚ Interval‚ Ordinal. These scales determines the tests to pick. L11.1: Data Analysis Procedures‚ Reporting Read: Slides‚ Chapter 19 pp648-653‚ Chapter 15 pp478-493 o Data Analysis Procedure: pp478 o Validation and Editing: pp478-486 (NOT Required for Final Exam) o Coding: pp486-490 o Data Cleaning: pp491-493 (NOT Required for Final Exam)
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look at the general idea of a confidence interval. The General Idea of Confidence Intervals Suppose that we have a population which is normally distributed. The population mean‚ usually denoted by μ‚ will thus be at the peak of the distribution. Assume that we plot the sample means on the horizontal axis. The 95% confidence interval is that interval in which 95% of the sample means will be in. Since the
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Retrieval T score for Patient 5 above or below the mean for the norm of the group? Provide a rationale for your answer. 6. Assuming that the distribution of the preoperative CVLT Retrieval T scores is normal‚ the middle 68% of the patients had T scores between what two values? 7. Assuming that the distribution of scores for the postoperative CVLT Retrieval T scores is normal‚ the middle 68% of the patients had T scores between what two values? 8. The researchers state that it appears that the functional integrity
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Practice Question #1: A gambler claims he can predict the roll of a die more often than chance would predict. To test this‚ a die is rolled 100 times and the gambler guesses the number that comes up twenty times and guesses incorrectly the other eighty times. Is this strong evidence that the gambler’s claim is true? a. Specify the null and alternative hypothesis for this problem. p = probability gambler guess correctly for an individual roll null (Ho): p = 1/6 alternative (Ha): p > 1/6 b
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