organization‚ analysis‚ interpretation‚ and presentation of data. It provides a more accurate way of expressing data rather than mere observation. This experiment used the different statistical concepts such as the Q test‚ mean‚ standard deviation‚ relative standard deviation‚ range‚ relative range‚ and confidence limits or confidence intervals. The results generated from these tests are used as a basis to check whether the values obtained from weighing 10‚ 25 centavo coins using an analytical balance and
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Terms: Forecast vs Forecast Error We clarify the terms used in the practice problems and the final exam problems. Some statisticians speak of the standard deviation or variance of the forecast. The forecast here is the distribution of future values. It is a random variable‚ which has a standard error (standard deviation and variance). Other statisticians use the term forecast for the mean of the distribution of future values. The forecast error (the error term in the forecast) is the distribution
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no mode because there is no value of the observation that appears most frequently. Every value appears only once. • Mean Deviation • Coefficient of the Mean Deviation (it is the Mean Deviation divided by the Mean) • Population Variance • Population Standard Deviation • Coefficient of Variation of the Standard Deviation (Standard Deviation divided by the Mean b. Comment on your findings. What does all of this mean? The population mean is the average
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Study #1 1) In order to calculate the expected return‚ risk premium‚ and standard deviation of the portfolio invested partly in the market and partly in Pioneer‚ we first needed to devise a table with all of the known variables: Table 1 Pioneer Gypsum (X) Market (Y) Expected Return 11.0% 12.5% Standard Dev. 32% 16% Beta 0.65 N/A The calculation of the expected return‚ risk premium and the standard deviation of the portfolio are dependent upon the amount that John wants to invest. For example
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Joey Stevens QMM 240 TR 10:00-11:15 Computer Assignment #1 1. a. Excel Histograms Bins MPG | Frequency | 11 | 1 | 16 | 3 | 21 | 16 | 26 | 34 | 31 | 13 | 36 | 9 | 41 | 2 | 46 | 2 | Bins Weight | Frequency | 1300 | 1 | 1780 | 7 | 2260 | 18 | 2740 | 12 | 3220 | 22 | 3700 | 11 | 4180 | 7 | 4660 | 2 | b. I chose the number of classes based on the Sturges’ Rule table. I knew I had 80 observations so that put me between either 7 or 8
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Non Performing Assets (npa) in sbi Getting current updates and regulations for the non performing assets (npa) in sbi With a steep rise in the ratio of the nonperforming assets all over the country‚ it has been really tough for the RBI to control and manage in the given time frame. No doubt‚ public sector banks including SBI have been in the list of banks that have been implementing the procedures to control the default line of the borrowers. On the other hand‚ it should also be noted that nonperforming
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X - X 2/ n-1 = {(84-86)2 + (87-86)2 + (84-86)2 + (88-86)2 + (85-86)2 + (90-86)2 + (91-86)2 + (83The standard deviation = √8.89 = 2.98 The coefficient of variation = 2.98/86 * 100% = 3.47% 86)2 + (82-86)2 + (86-86)2 } / (10 -1) = 8.89 d. f. 2. In 2008‚ the average age of students at GUST was 22 with a standard deviation of 3.96. In 2009‚ the average age was 24 with a standard deviation of 4.08. In which year do the ages show a more dispersed distribution? Show your complete work and support your
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) − (1 − α)σ (RB )]2 . Therefore‚ the standard deviation of portfolio P is σ (RP ) = ασ (RA ) − (1 − α)σ (RB ). As assets A and B are perfectly negatively correlated‚ we can construct portfolio P such that its standard deviation is 0. The weights of such portfolio are 0 = ασ (RA ) − (1 − α)σ (RB ) = 0.14 × α − 0.23 × (1 − α). Solving the above equation for α gives α= 0.23 = 0.622. 0.14 + 0.23 Portfolio P with standard deviation zero has weight 0.622 on asset A and weight 0.378
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Descriptive statistics information Descriptive statistics organize‚ summarize‚ and communicate a group of numerical observations and describe large amounts of data in a single number or in just a few numbers Inferential statistics Use samples to draw conclusions about a population Inferential statistical use sample data to make general estimates about the larger population‚ and infer or make an intelligence guess about‚ the population Sample: a set of observations drawn from the population
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Project in Math Statistical Data Concerning the Height of BSDAS Academy Department Students S.Y. 2013-2014 Made by: Kent Irvin Pastrana Miguel Pump Adawan Christian Yango Presented to Wayne B. Valera on the day of March 24‚ 2014 I. Abstract Many times‚ people would ask what another person’s height is‚ and joke or say wow depending on the answer. Height is important in our lives; it allows us to reach higher (yes‚ literally)‚ see farther (yes‚ literally again) and
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