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 data which are mutually exclusive Frequency distribution - a grouping of data into classes Relative frequency distribution - calculates the
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GPA reported. The hours or sleep and the GPA of the students were entered into SPSS ’s spread sheet and are shown on the next page. E720 Notebook Assignment: Correlation Kandell 2 Dependent and Independent Variables In correlational analysis we do not call one variable dependent and the other independent. However‚ Hours of sleep will be placed on the X-axis (abscissa) and GPA will placed on the Y-axis (ordinate) Is there a correlation between Hours of sleep and GPA in graduate students
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University of Southern California Department of Economics ECON 317 Introduction to Statistics for Economists Prof. Safarzadeh Assignment # 2 Student Name: ________________ Answer all the questions on the spaces provided. Underline your answers and show your calculations and work on the tables. Item |Speed |Mileage | | |X - X |(X- X)2 |(Y-Y) |(Y-Y)2 |(X-X)(Y-Y) | | | |1 | 30 | 25 | | | | | | | | | | |2 | 50 | 20 | | | | | | | | | | |3 | 35 | 23 | | | | | | | | | | |4 | 45 | 21 | |
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been 10% of the number of employees in a given year. 2) The number of workplace injuries‚ X‚ typically follows a Poisson distribution with a parameter λ‚ where E(X) = λ and Variance(X) = λ. 3) We can reasonably approximate the Poisson distribution via a Normal distribution‚ with the same expected value and variance (according to Central Limit Theorem‚ for which you don’t need to know the details). 4) You will also need to use the critical value for the standard Normal distribution (i.e
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volume shifts to the right; (see the graph below) it may not be at the equilibrium but it’s getting closer to the equilibrium. (Period 2 production lies between period 1 and equilibrium production level) In the second half of the year‚ the labor variance looks worse than the first term. This is the result of an increase in production during second term. In the first half of the year‚ the company did not meet its production quota (therefore less materials and labor were used for production). So Carlo
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and (C) The range of the data that would contain 68% of the results. (5 points). Raw data: sales/month (Millions of $) 23 45 34 34 56 67 54 34 45 56 23 19 Descriptive Statistics: Sales | Variable | Total Count | Mean | StDev | Variance | Minimum | Maximum | Range | Sales | 12 | 40.83 | 15.39 | 236.88 | 19.00 | 67.00 | 48.00 | Stem-and-Leaf Display: Sales Stem-and-leaf of Sales N = 12 Leaf Unit = 1.0 | 1 | 1 | 9 | 3 | 2 | 33 | 3 | 2 | | 6 |
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Observation = estimated relationship + residual: yi =+ ei => yi = b1 + b2 x + ei Assumptions underlying model: 1. Linear Model ui = yi - 1- 2xi 2. Error terms have mean = 0 E(ui|x)=0 => E(y|x) = 1 + 2xi 3. Error terms have constant variance (independent of x) Var(ui|x) = 2=Var(yi|x) (homoscedastic errors) 4. Cov(ui‚ uj )= Cov(yi‚ yj )= 0. (no autocorrelation) 5. X is not a constant and is fixed in repeated samples. Additional assumption: 6. ui~N(0‚ 2) => yi~N(1- 2xi‚ 2)
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Part 1 of 1 - | Question 1 of 10 | 1.0 Points | Consider the following scenario in answering questions 1 through 4. Results from previous studies showed 79% of all high school seniors from a certain city plan to attend college after graduation. A random sample of 200 high school seniors from this city reveals that 162 plan to attend college. Does this indicate that the percentage has increased from that of previous studies? Test at the 5% level of significance. State the null and alternative
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of paper. Please highlight your answers so we can find them easily. 1. Compute and report the mean returns‚ variances‚ and standard deviations for the two stocks. In addition‚ compute the covariance and the correlation between the two stock returns. Report all numbers as annualized. (Hint: annualized variance is equal to 12*monthly variance. Also‚ please do not report variances and covariances in %‚ which would not make sense.) 2. Plot the mean-standard deviation graph for a portfolio
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been reviewing random variables. RVs have certain properties such as mean that measures the center‚ and variance that measures the dispersion. We would like to make claims about these properties and test them using statistical methods. Over the past years‚ Wall Street has been very interested in the volatility of the stocks. In this case‚ we would want to make sound claims about variances. We start with a null hypothesis Ho‚ which is the claim that we will test. It looks as such: In this
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