draw conclusions. So what are descriptive and inferential statistics? And what are their differences?We have seen that descriptive statistics provide information about our immediate group of data. For example‚ we could calculate the mean and standard deviation of the exam marks for the 100 students and this could provide valuable information about this group of 100 students. Any group of data like this‚ which includes all the data you are interested in‚ is called a population. A population can be
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5 to size 14 amongst the participants. With these ranges‚ the mean is 9.142‚ with a standard deviation of 2.583 and a variance of 6.670. Appendix B: Male vs. Female data sets‚ show the mean‚ standard deviation and variance for both of these sets respectively. Female data sets have a mean of 7.111‚ standard deviation of 1.131‚ and a variance of 1.281 whereas the males have a mean of 11.294‚ a standard deviation of 1.803‚ and a variance of 3.251. The T-test was applied to these two data sets to
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cluster between $1‚000 and $2‚250. The standard deviation of the checking account balances 596905 and the range is 2525. The first quartile shows that 25 percent of the data are lower 1122.50 and the third quartile shows that 75 percent of the data are lower 1935.50. The standard deviation is the positive square root of the variance. It is a measure of variability used in statistics. It shows how much variation exists from the average. A low standard deviation indicates that the data points tend to
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Creating efficient frontiers using excel. Suppose we have 3 risky assets whose net return has the mean vector and variancecovariance matrix given below: Asset Mean VarianceCovariance Matrix 1 2 3 0.06 0.12 0.03 1 0.3 0.3 0.3 1 0.3 0.3 0.3 1 Weights Ones Mean Portfolio Return 1 1 1 0.176666122 Portfolio Portfolio Portfolio Variance STD Constraint 2.42961 1.558721 1 0.079372 1.603166 -0.68254 To model the portfolio choice problem‚ I begin by highlighting the mean vector and giving
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Release date: 27 April 2014 Submission date: 9 May 2014 TUTORIAL ON HYPOTHESIS TESTING (1) Basic Concept 1. State the null and alternative hypothesis for each conjecture : a. A researcher thinks that if expectant mothers use vitamin pills‚ the birth weight of the babies will increase. The average birth weight of the population is 3.0kg. b. An engineer hypothesizes that the mean number of defects can be decreased in a manufacturing process of compact disks by using robots instead of humans
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different tools to scrutinize the market and identify the most succulent securities available for their clients‚ to accomplish this objective they utilize different mathematical and statistical calculations like arithmetic mean‚ geometric mean and standard deviation‚ this paper shows how to perform these calculations and how they could be used to identify a good investment. Additionally‚ provides an overview in formulating and justifying investment policies identifying objectives and constraint considerations
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1 2 0u p to 1 40 1 4 0 u p to 1 60 1 6 0u p to 1 80 1 8 0u p to 2 00 I | | | | 8 12 16 7 4 questions. Basedon the abovedata‚answer following the i. phone th C a l cu l a te e me a nof the m obile bills. [3 marks] ii. the Calculate standard deviation. [3 marks]
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Normal Distribution Normal distribution is a statistics‚ which have been widely applied of all mathematical concepts‚ among large number of statisticians. Abraham de Moivre‚ an 18th century statistician and consultant to gamblers‚ noticed that as the number of events (N) increased‚ the distribution approached‚ forming a very smooth curve. He insisted that a new discovery of a mathematical expression for this curve could lead to an easier way to find solutions to
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Variables Graphs Measurement scales Nominal Ordinal Interval Ratio Qualitative Quantitative Independent Dependent Bar Graph Histogram Box plot Scatterplot Measures of Center Spread Shape Mean Median Mode Range Variance Standard deviation Skewness Kurtosis Tests of Association Inference Correlation Regression Slope y-intercept Central Limit Theorem Chi-Square t-test Independent samples Correlated samples Analysis-of-Variance Glossary of Terms
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Omkar & Yaying Wednesday 5-6pm WEEK 3 BES PASS Descriptive Statistics Population - a set of all possible observations. Sample - a portion of a population. We often use information concerning a sample to make an inference (conclusion) about the population. Parameter - describes a characteristic of the population‚ eg: the population variance Statistic- describes a characteristic of a sample‚ eg: the sample variance Frequency Distribution and Histograms Class - a collection of
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