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    Thesis Computer Enrollment

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    findings also showed that 25 or 50% of the respondents were 3 rd year and 25 or 50% were 4 th year. This means that the frequency and the percentage of the respondents coming from the 3 rd year and 4 th year level were equal. The findings also showed the percentage that 22 or 44% of the respondents were Computer Science students and 28 or 56% were Business Administration students. This means that majority of the

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    Statistics

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    of measurement MEAN Mean: a first a first measure of central tendency for the sample: for the population: Characteristics of the mean: * Changing a score will change mean * Adding or removing a score will change mean (unless the score is equal to mean) * Adding‚ subtracting‚ multiplying‚ dividing each score by a constant value causes mean to change accordingly * Sum of differences from the mean is zero: * Sum of squared differences from the mean is minimal or Sum

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    golfers for a particular course has a mean of 70 and a standard deviation of 3.0. Suppose 36 golfers played the course today. Find the probability that the average score of the 36 golfers exceeded 71. 2) At a computer manufacturing company‚ the actual size of computer chips is normally distributed with a mean of 1 centimeter and a standard deviation of 0.1 centimeter. A random sample of 12 computer chips is taken. What is the probability that the sample mean will be between 0.99 and 1.01 centimeters

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    Results and Discussion

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    working in industries. Table 4.1.1.Indicating the mean‚ standard deviation and the Z- score for stress among males and females employees working in industries. Variables | N | Mean | Standard Deviation | Z- score | Males | 100 | 139.33 | 18.276 | 2.525 | Females | 100 | 146.08 | 19.514 | | Table 4.1.1. Illustrates the mean‚ standard deviation and the Z-score for stress of 100 males and 100 females (N=200). As shown in the table the mean score for stress among males and females is139.33

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    interval estimate of the population mean sales price and population mean number of days to sell for Gulf View condominiums. Also‚ interpret the results. 5. A 95% confidence interval estimate of the population mean sales price and population mean number of days to sell for Gulf View condominiums. Also‚ interpret the results. Also‚ consider the following scenario and include your responses in your Report: 6. Assume the branch manager requested estimates of the mean selling price of Gulf View condominiums

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    meaningful essential can be extracted from it. The most commonly measures of central tendency are the mean‚ median‚ and mode. Properties of the Arithmetic Mean      easy to compute easy to understand valuable in statistical tool strongly influence by extreme values‚ this is particularly true when the number of cases is small cannot be compute when distribution contains open-ended intervals Uses of Mean     for interval and ratio measurement when greatest sampling stability is desired when

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    Stream Ecology Results

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    number of organisms and families of macroinvertebrates along with the calculated data can be seen in Table 1. Other sets of data was recorded and compared to test the stream quality at Pricket’s Creek. The water temperatures (°C) were 16.76 ± 2.32 (mean ± St. Dev.) above‚ 15.50 ± 2.47 at‚ and 16.18 ± 2.70 below (Figure 1). The dissolved oxygen content values (ppm) were 6.78 ± 3.03 above‚ 7.88 ± 2.04 at‚ and 8.15 ± 1.54 below (Figure 2). The pH values were 7.15 ± 0.96 above‚ 7.88 ± 2.04 at‚ and 7.46

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    Simulation

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    Management Simulation Debrief Slides ©© Enspire Enspire Learning Learning and and Harvard Harvard Business Business School School (revised Dec 2010) 1 Board Members’ Objectives Member Objective Betty Forecasting: choice of options (consensus vs. mean) Doug Forecasting: choice of options (role of risk) Yvonne Stocking Levels: Weighing the costs of over/understocking Meryl Production flexibility: accurate response/ sourcing strategy (focus on flexibility) Paul Production flexibility: accurate

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    QMS102 Cribsheet final

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    - Statistics is the science of collecting organizing‚ presenting‚ analyzing and interpreting data. It turns Data into information through transformation. Population ! - Everyone in group ! ! - µ is the mean ! - σ is the standard deviation Sample! - Some/Portion of group ! -x is the mean!! -S is the standard deviation Measurement Scales Types of Data Categorical/Qualitative Categorical/Qualitative Nominal! -Data has category but no order Data that can only be in categories ! ! -Example

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    Bootstrap codes

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    11:18)] k200rt<-data[‚c(1‚19)] unhedgert<-data[‚c(1‚20)] head(unhedgert) #Hedge portfolio ---QUESTION: THE HEDGE SHOULD BE DONE WITH THE PARAMETERS OF THE RETURNS OF EACH ASSETS OR FROM THE HEDGE PORT------ Expr<- sapply(asret‚mean) #Calculating the expected return (Just the mean of the each of the assets) sdh<- sapply(asret‚sd) #Calculating the Standard deviation. varh<-sapply(asret‚var) covmat<-cov(asret) cormat<-cor(asret) ncol(asret) library(PerformanceAnalytics) library(tseries) library(quadprog)

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