The population standard deviation σ of a discrete random variable ‚ Measure how close a random variable tends to be the population mean μ‚ so you must understand μ before you understand σ If you have a random variable like a bet at a casino or and investment then the standard deviation σ measure the risk‚ if there is a lot of risk then the standard deviation is high The formulas for standard deviation are given below but you should look at the examples first Population mean Population variance
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A. What is the mean age of this sample? What is the standard deviation? The mean age is 47.5 years old. The standard deviation is 10.74832 years. http://www.calculator.net/standard-deviation-calculator.html Sample Standard Deviation‚ s: 10.748316881702 Sample Standard Variance‚ s2 115.52631578947 Total Numbers‚ N 20 Sum: 950 Mean (Average): 47.5 Population Standard Deviation‚ σ 10.476163419878 Population Standard Variance‚ σ2 109.75 If it follows the normal distribution The
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A business graduate very much wants to get a job in any one of the top 10 accounting firms. Applying to any of these companies requires a lot of effort and paperwork and is therefore costly. She estimates the cost of applying to each of the 10 companies and the probability of getting a job offer there. These data are tabulated below. The tabulation is in the decreasing order of cost. 1. If the graduate applies to all 10 companies‚ what is the probability that she will get at least one offer
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following for the data in Column K‚ “The degree of agreement among patrons that Remington’s has large portions‚” on the Remington Data worksheet of the Remington’s Data Set workbook: Mean -3.26 Standard deviation-0.911 Range -3 4 Mean 3.261306533 Standard Error 0.064596309 Median 4 Mode 4 Standard Deviation 0.911243075 Sample Variance 0.830363941 Kurtosis -1.16899198 Skewness -0.663704706 Range 3 Minimum 1 Maximum 4 Sum 649 Count 199 Largest(1) 4 Smallest(1) 1 Confidence Level(95.0%) 0.12738505
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References: Anderson‚ D.R.‚ Sweeney‚ D. J.‚ & Williams‚ T. A. (2003). Essentials of Statistics for Business and Economics (3rd ed.). Mason‚ OH: South-Western. Becker‚ W. S. & Wellins‚ R. S. (1990‚ March). Customer-Service Perceptions and Reality. Training and Development Journal‚ 44(3)‚ 49. Retrieved August 1‚ 2011‚ from ABI/INFORM Global. (Document
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Mean and Standard Deviation The mean‚ indicated by μ (a lower case Greek mu)‚ is the statistician ’s jargon for the average value of a signal. It is found just as you would expect: add all of the samples together‚ and divide by N. It looks like this in mathematical form: In words‚ sum the values in the signal‚ xi‚ by letting the index‚ i‚ run from 0 to N-1. Then finish the calculation by dividing the sum by N. This is identical to the equation: μ =(x0 + x1 + x2 + ... + xN-1)/N. If you are not
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the actuarial field and finds the average salary to be $41‚000. The population standard deviation is $3000. Can her claim be supported at 0.05? x¯=14.7‚ μx¯=13.77‚ ox¯=5.34‚ n=29‚ α=.01 3. Monthly Home Rent. The average monthly rent for a one bedroom in San Francisco is $ 1229. A random sample of 15 one bedroom homes about 15 miles outside of San Francisco had a mean rent of $1350. The population standard deviation is $250. At a=0.05 can we conclude that the monthly rent outside San Francisco
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Standard deviation is the square root of the variance (Gravetter & Wallnau‚ 2013). It uses the mean of the distribution as a reference point and measures variability by considering the distance of each score from the mean. It is important to know the standard deviation for a given sample because it gives a measure of the standard‚ or average‚ range from the mean‚ and specifies if the scores are grouped closely around the mean or are widely scattered (Gravetter & Wallnau‚ 2013). The standard deviation
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x can be included in y f. Represents the simplest measure of spread (or variability) g. Indicates the most frequent observation in a frequency distribution h. Represents a theoretical family of distributions that may have any mean or any standard deviation i. Indicates how widely the out around the measures of central tendency j. Measure an event over time B. Match the following data display tools with their descriptions. (Descriptions may be used more than once or not at all.) A horizontal
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sold‚ and that units left unsold at the end of the season were sold at a loss that average 8 percent of wholesale price. Therefore‚ the stock out probability equal to 8%/(24%+8%)=25% so there are 75% probability of being less than mean+0.67*SD (standard deviation). According to z table‚ z equal to 0.67 when probability is 0.75. Therefore‚ we can calculate quantity for each style include the risk of stock out by using formulate Q*=mean+z*SD. Therefore‚ we can get the maximum order units for each style
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