statistics Mean: 2 Median: 2 sum of squared deviations: 56 Variance: 2.8 standard deviation: 1.67332 12. Calculate descriptive statistics Mean: 1‚112 the mean is 56.5; 1‚1245 the mean is 123; 1‚1361 the mean is 181; 1‚1372 the mean is 186.5; 1‚1472 the mean is 236.5 Median: 1‚112 the median is 56.5; 1‚1245 the median is 123; 1‚1361 the median is 181; 1‚372 the median is 186.5; 1‚1472 the median is 236.5 sum of squared deviations: 1‚112 is 6160.5; 1‚1245 is 29768; 1‚361 is 64800;
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confidence intervals verses point estimates? The sample mean is a point estimate (single number estimate) of the population mean – Due to sampling error‚ we know this is off. Instead‚ we construct an interval estimate‚ which takes into account the standard deviation‚ and sample size. – Usually stated as (point estimate) ± (margin of error) • What is meant by a 95% confidence interval? That we are 95% confident that our calculated confidence interval actually contains the true mean. • What is the
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CHAPTER 22 estimating risk and return on assets 1. WHAT IS RISK? Risk is the variability of an asset’s future returns. When only one return is possible‚ there is no risk. When more than one return is possible‚ the asset is risky. The greater the variability‚ the greater the risk. 2. RISK – RETURN RELATIONSHIP Investment risk is related to the probability of actually earning less than the expected return – the greater the chance of low or negative returns‚ the riskier the investment
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client can quickly learn whether the process is operating satisfactorily or corrective actions needs to be taken. Summary of Statistics Sample 1 Sample 2 Sample 3 Sample 4 Mean 11.96 12.10 12.14 12.15 Standard Error 0.04 0.04 0.04 0.02 Standard Deviation 0.22 0.23 0.23 0.16 Sample Variance 0.05 0.05 0.05 0.03 Sum 358.69 362.90 364.08 364.46 From the summary of statistics we can see that mean has an upward trend. Mean value differ from sample to sample. Here
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predictive statistical research. Standard deviation is a measure of the data spread and it is signified by the Greek letter sigma (σ). The standard deviation requires calculation of the average‚ compare each respondent’s value to the average‚ and square that difference (Burns & Bush‚ 2012‚ pg. 252). Therefore‚ the formula for standard deviation is the square root of the variance. The variance is the average of the squared differences of the mean. The standard deviation explains the density of data scattered
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called as standard normal. Normal distribution problems and solutions – Formulas: X < μ = 0.5 – Z X > μ = 0.5 + Z X = μ = 0.5 where‚ μ = mean σ = standard deviation X = normal random variable Normal Distribution Problems and Solutions – Example Problems: Example 1: If X is a normal random variable with mean and standard deviation calculate the probability of P(X<50). When mean μ = 41 and standard deviation = 6.5 Solution: Given Mean μ = 41 Standard deviation σ = 6.5 Using
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of 25% (Anderson‚ Sweeney‚ & Williams‚ 2012). The measure of variability is expressed through an element of dispersion across a population sample. Variability is measured through the calculation of range‚ interquartile range‚ variance‚ standard deviation‚ and coefficient of variation. The range is not commonly used as it is influenced significantly by outliers; however‚ it is measured by the subtracting the smallest value by the largest value. Interquartile range represents the difference
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variance (or standard deviation) of real estate returns and the correlation between real estate returns and returns for each of the other asset classes. (Note that the correlation between real estate returns and returns for cash is most likely zero.) 3. (a) Answer (a) is valid because it provides the definition of the minimum variance portfolio. 4. The parameters of the opportunity set are: E(rS) = 20%‚ E(rB) = 12%‚ σS = 30%‚ σB = 15%‚ ρ = 0.10 From the standard deviations and the correlation
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higher standard deviation and the higher variance. If we compare both stocks‚ Reynolds is riskier than Hasbro in this case. The higher variance indicates higher chance that the actual return on Reynolds will deviate from the expected return. S&P 500 REYNOLDS HASBRO Mean/Average 0.574333 1.874833 1.183833 Variance 12.972333 87.730541 65.866763 Standard Deviation 3.601713 9.366458 8.115834 Answer 2. At individual stock level‚ Reynolds fluctuates more than Hasboro as it has higher Standard Deviation
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and standard deviation of the probability distribution created by rolling a die. Either show work or explain how your answer was calculated. Descriptive Statistics: Die1 Variable Mean StDevDie1 3.450 1.317Mean: 3.50 Standard deviation: 1.317Calculations were derived by using the minitab and going into the Stat > Basic Statistics > Display Descriptive Statistics > Variables than select the C14 (Die1) > below enter the statistics and check mark only mean and standard deviation
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