between hv and lv in data set. | | | | Variance | population (δ2) | =∑(x-x)2N | x – classmarkx –meanN - population | Average squared deviation from the mean. | | | | | sample(s2) | =∑(x-x)2n-1 | x – classmarkx –meann - sample | | | | | Standard Deviation | population (δ) | =∑(x-x)2N | | is square root of the average deviation from the mean‚ or simply the square root of the variance. | Square root lang yung result ng variance | | | | sample(s) | =∑(x-x)2n-1 | |
Premium Standard deviation Statistics Pearson product-moment correlation coefficient
possible outcome. (3)Standard Deviation of Return: Risk refers to the dispersion of a variable. It is commonly measured by the variance or the standard deviation. The variance of a probability distribution is the sum of the squares of the deviations of actual returns from the expected return‚ weighted by the associated probabilities. 2 = ∑ p(i)*{*R(i)-E(R)]} 2 where‚ 2 =variance‚ R®=return for the ith possible outcome‚ p(i)=probability
Premium Normal distribution Variance Investment
Practice Quiz I 1. The following bar chart describes the results of a survey concerning the relevance of study to present job by school. Focus on the School of Business and Management. What are the mode and the median respectively? (a) Relevant‚ Neutral (b) Relevant‚ Relevant (c) Neutral‚ Relevant (d) Neutral‚ Neutral 2. Some graphical descriptions of final examination scores for students of a Statistics course are given below. Please indicate which one is false. (a) (b) (c)
Premium Variance Standard deviation Random variable
Contents Univariate Data 2 Central tendency 2 Mean 2 Median 3 Mode 3 Trimean 3 Trimmed Mean 3 Spread 3 Range 3 Semi Inter Quartile Rang 3 Variance and Standard Deviation 3 Skew 3 Graphical Representations 4 Frequency Polygons& Cumulative Frequency Polygons 4 Histograms & Bar Graphs 4 Stem and Leaf plots 4 Box Plots 4 Describing Bivariate Data 4 Scatterplots 4 Pearson’s Correlation 4 Spearman’s Rho 4 Probability 4 Binomial Distribution 4 Assumptions:
Premium Normal distribution Standard deviation Arithmetic mean
Version 1 FINANCE 261 FINANCE 261 Test Answer Sheet Name: __________________________________________ Student ID Number:_______________________________ Please use CAPITAL LETTERS when writing your answers. Question Answer Question Answer Question Answer 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Question Answer 16 17 18 19 20 1 Version 1 FINANCE 261 THE UNIVERSITY OF AUCKLAND Department of Accounting and Finance FINANCE
Premium Stock market Stock Investment
Convert Monthly to Annual Returns and Standard Deviations: Annual Mean Return: RA=12*RM Annual Standard Deviation: STDEVA= 12* VarM= 12*STDEVM 4. Portfolio (equally weighted): Monthly Return: RP= iwiRi equally weighted: RP= 110iRi → AVERAGE Variance: VarP= ijwiwjCovi‚j equally weighted: VarP= (110)2ijCovi‚j Covariance Matrix: Cov1‚1⋯Cov1‚n⋮⋱⋮Covn‚1⋯Covn‚n → symmetric Create Covariance Matrix: Two Options: 1. Data Analysis (Add-In Tool) (indirectly‚ returns population covariance)
Premium Standard deviation Variance
ETF2121/ETF5912 Data Analysis in Business Unit Information – Semester 1 2014 Coordinator and Lecturer - Weeks 7-12: Associate Professor Ann Maharaj Office: H5.86 Phone: (990)32236 Email: ann.maharaj@monash.edu Lecturer - Weeks 1-6: Mr Bruce Stephens Office: H5.64 Phone: (990)32062 Email: bruce.stephens@monash.edu Unit material: No prescribed textbook Unit Book: available on the Moodle site. Exercises: available on the Moodle site. Software: EXCEL. Recommended Reference Books Berenson
Premium Statistics Statistical inference Regression analysis
Gauss Markov Theorem In the mode [pic]is such that the following two conditions on the random vector [pic]are met: 1. [pic] 2. [pic] the best (minimum variance) linear (linear functions of the [pic]) unbiased estimator of [pic]is given by least squares estimator; that is‚ [pic]is the best linear unbiased estimator (BLUE) of [pic]. Proof: Let [pic]be any [pic]constant matrix and let [pic]; [pic] is a general linear function of [pic]‚ which we shall take as an estimator of [pic]. We must specify
Premium Function Variance Estimator
York‚ and 20 were residents of North Carolina. From the data collected we could know that the higher test scores indicate higher levels of depression. The descriptive statistics of the data collected are as following: GROUPS SIZE SUM MEAN SAMPLE VARIANCE FLORIDA 20 88.50 4.42 3.81 NEW YORK 20 131.53 6.58 3.95 NORTH CAROLINA 20 137.09 6.85 2.31 For the second part of this study‚ we considered the relationship between geographic location and depression for individuals 65 years of age or older
Premium Statistics Arithmetic mean Statistical hypothesis testing
by the “LESS THAN OGIVE” graph. Mean Pocket Money of Students ( Computation of Sample Mean from Grouped Data) Mean( x’)= Summation(fiMi) / n = 3967.17 Sample Variance of Pocket Money received by IFIM Students: Sample Variance s2 = Summation (fi(Mi – x’)2) / n – 1 = 55466666.7 / 30 – 1 = 1912643.68 Stating the variance gives an impression of how closely concentrated round the expected value the distribution is; it is a measure of the ’spread’ of a distribution about its average value
Premium Standard deviation Arithmetic mean Variance