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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determine that g was 9.7993 ± 0.0010 m/s2 which was 0.0653 % from the known value. If we took into account the period difference‚ we found that g was 9.7982 ± 0.0083 m/s2 which is 0.0552 %. Both methods gave us results well within our goal of 0.2% deviation from the expected value. I. INTRODUCTION is equal to τ = I0 α (II.2) In the course of the author’s physics degree‚ no constant has been so ubiquitous as the local acceleration due to gravity. As such‚ it proves an important pedagogical
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STATISTICS - Lab #6 Statistical Concepts: Data Simulation Discrete Probability Distribution Confidence Intervals Calculations for a set of variables Open the class survey results that were entered into the MINITAB worksheet. We want to calculate the mean for the 10 rolls of the die for each student in the class. Label the column next to die10 in the Worksheet with the word mean. Pull up Calc > Row Statistics and select the radio-button corresponding to Mean. For Input variables:
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comparison between results‚ as initial values may have been different. Standard Deviation This measures the spread of data‚ and it can only be calculated when there is more than one repeat. The larger the standard deviation‚ the more widely spread the data is and therefore you have a less reliable mean. You can compare the standard deviation of two different sets of data‚ if the two standard deviation values
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locates the center of a distribution of values. The three types of the central tendency are the mean‚ the median and the mode. Secondly‚ we will look at the dispersion which is the spread of values around the central tendency (Dodge 2003). The standard deviation is a more accurate way of measuring the dispersion. Thirdly‚ the use of graphics and tables to illustrate the data collected in a visual background. Fourthly there is the frequency distribution. In the frequency distribution is a summary
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provided in section E4.4 of the Excel notes in the Software Information Folder under Week 0 on Moodle. (a) Use the Excel function NORM.S.DIST to calculate the following probabilities to four decimal places‚ where the random variable Z follows a standard normal distribution. Write your answers to four decimal places on this sheet and remember to draw the curves? For every second question‚ please use your tables to find the probability as well as Excel. (i) P(Z 0.443) (ii) P(Z <1.522) =
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a. x-bar = (157+132+109+145+125+139)/6=$134.5 s^2 = ((157-134.5)^2+(132-134.5)^2+(109-134.5)^2+(145-134.5)^2+(125-134.5)^2+(139-134.5)^2)/5 = $276.7 s=sqrt(s^2) = sqrt(276.7) =$ 16.634 b. 69.26% of the expense would fall within 1 standard deviation from the mean -> 134.5+/- 16.634 =
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because most of the salaries are less than $1‚000‚000. Standard Salaries Data Mean- $2‚006‚742.122 Median- $1‚016‚630 Standard Deviation- $2‚741‚746.033 Salaries with $100‚000 Bonus Data Mean- $2‚106‚742.122 Median- $1‚116‚630 Standard Deviation- $2‚741‚746.033 With the $100‚000 bonus‚ the mean and the median increased by $100‚000‚ because we increased all the salaries by $100‚000. However‚ the standard deviation was not affected‚ because the distribution of data was not
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period is that the stark income differences across states have narrowed considerably: In 1939 the highest income state’s per capita personal income was 4.5 times the lowest‚ but by 1976 this ratio had fallen to less than 2 times. Since 1976‚ the standard deviation of per capita incomes at the state level has actually risen‚ as some higher-income states have seen their income levels rise relative to the median of the states. A better understanding of the sources of these relative growth performances should
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AP Statistics Quarter 1 Final (Chapters 1-5) Chapter 1 Sections 1.1 and 1.2 I. Observation vs. Experiment A. Observational study: Record data on individuals without attempting to influence the responses. We typically cannot prove anything this way. B. Experimental study: Deliberately impose a treatment on individuals and record their responses. Influential factors can be controlled. C. Confounding 1. Two variables (explanatory variables or lurking variables) are confounded when their effects
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