Scenario I Inputs -- Hypothesized Population Mean: 119155 <-- Input the appropriate number for your situation Population Standard Deviation (sigma): 30000 <-- Input the appropriate number for your situation Sample size (n): 300 <-- Input the appropriate number for your situation Sample Mean (X-bar) 124450 <-- Input the appropriate number for your situation Intermediate Calculations -- Standard Error of the Estimate: 1732.0508 Test Statistic (z): 3.0570697 Results --
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Strength vs. reliability of a relation between variables Why stronger relations between variables are more significant Why significance of a relation between variables depends on the size of the sample Example: "Baby boys to baby girls ratio" Why small relations can be proven significant only in large samples Can "no relation" be a significant result? How to measure the magnitude (strength) of relations between variables Common "general format" of most statistical tests How the "level
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Central Measures Measures of central tendencies are nothing but the measures to describe the "central" values of a collected sample. For an ungrouped set of data these measures are: the mean‚ the median‚ and the mode. The Mean The arithmetic mean‚ or the simple mean‚ is computed by summing all numbers in an array of numbers (xi) and then dividing by the number of observations (N) in the array. ; the sum is over all i’s. The mean uses all of the observations‚ and each observation affects the
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Practice Multiple Choice Questions for Exam 2 Prof. Alex Angelus Sept. 20‚ 2014 Question 1 2. Which of the following regarding the mean and variance of a portfolio of two stocks is false? a. . b. . \ c. d. . 2 Question 2 2. Which of the following are required conditions for the distribution of a discrete random variable X that can assume values xi? a. 0 p(xi) 1 for all xi b. c. Both a) and b) are required conditions d. Neither a) nor b) are required conditions
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Executive Summary This report aims to provide statistical analysis on the Efficiency and Effectiveness of AllRepair’s staff. Using sample data from 293 jobs completed in the last year‚ we were able to make accurate inferences concerning AllRepair’s business and have formed the following conclusions; Efficiency Our analysis of efficiency was primarily concerned with finding any marked differences between staff undertaking the same tasks. We found that; * For jobs assigned a low-level or
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Eulogio “Amang” Rodriguez Institute of Science and Technology Nagtahan‚ Sampaloc‚ Manila College of Education Doctor of Education Major: EDUCATIONAL MANAGEMENT Subject: Seminar in Project Development‚ Industrial Planning Design‚ Implementation and Evaluation Professor: Dr. Elidio T. Acibar Reporter: Evelyn L. Embate Topic: Sampling SAMPLING Measuring a small portion of something and then making a general statement about the whole thing. Advantages of sampling Sampling makes possible
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Simplified Formula For Proportions Yamane (1967:886) provides a simplified formula to calculate sample sizes. This formula was used to calculate the sample sizes in Tables 2 and 3 and is shown below. A 95% confidence level and P = .5 are assumed for Equation 5. [pic]Equation 5. Where n is the sample size‚ N is the population size‚ and e is the level of precision. When this formula is applied to the above sample‚ we get Equation 6. [pic] NURSES COMPRISE THE MAJORITY OF THE HUMAN HEALTH MANPOWER IN THE
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practice of methods used to determine the composition (quantity and nature) of matter. Analytical Chemistry involves separating‚ identifying‚ called qualitative analysis; and determining the relative amounts (concentration) of the components in a sample of matter‚ called quantitative analysis. There are several different areas of analytical chemistry‚ namely: environmental analysis‚ forensic analysis‚ clinical analysis‚ bioanalytical analysis‚ and pharmaceutical analysis. This introductory analytical
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> $520 B) C) Assumptions: 1) Simple Random Sample (SRS): We can assume that the sample was selected by random. 2) 10% Assumption: We can assume that the sample size (n=27) is less than 10% of the population. 3) Nearly Normal: n = 27‚ which is less than n=30. We need to look at the boxplot and histogram to determine if the sample is normal. The diagram shows that the sample data is skewed to the left‚ with an outlier at 200. The sample is not normal because the diagram is not unimodal
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Case Problem Set 3: Problem 1: Young Professional magazine was developed for a target audience of recent college graduates who are in their first 10 years in a business/professional career. In its two years of publication the magazine has been fairly successful. Now the publisher is interested in expanding the magazine’s advertising base. Potential advertisers continually ask about the demographics and interests of subscribers to Young Professional. To collect this information the magazine has
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