Interval: Stem and leaf displays, histograms, ogives, box and whisker plots • Measures of central location (mean, median, mode) • Measures of dispersion/spread (standard deviation, variance) Do 1.7.3 Quiz Can attempt all 1.7.4 Topic Questions Week 2 (Sampling, Probability, Normal Distribution) Sampling Concepts • Types of sampling plans (simple random sampling, stratified random sampling, cluster sampling Probability Concepts • From a table of joint probabilities
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From this case, there are two types of errors, which the consortium can make. A Type I Error is referred to as a “false positive.” A Type I error would be made when the null hypothesis is rejected when it should be accepted. This error may occur if the consortium defends any lawsuit against them if they are using 6% (6/100) as their surveying result. The results of the sample size of 100 people indicate that the percentage range is from 1.35% to 10.65%. The test results can be higher than 10%, but
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3. Ralph Winkler Problem 2 The 2002 New York City Housing and Vacancy Survey showed a total of 59,324 rent-controlled housing units and 236,263 rent-stabilized units built in 1947 or later. For these rental units, the probability distributions for the number of persons
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=SUMPRODUCT(weights, values) / n Where n = SUM(weights) Median =MEDIAN() Mode =MODE() Range =MAX()-MIN() Class Width =range / number of classes All Versions of Excel Excel 2010 Variance Sample: =VAR() =VAR.S() Population: =VARP() =VAR.P() Standard Deviation (SD) Sample: =STDEV() =STDEV.S() Population: =STDEVP() =STDEV.P() Or,=SQRT(variance) Or, =variance^0.5 Skewness =3*(AVERAGE() - MEDIAN()) / SD Coefficient of Variation =SD / AVERAGE() * 100 Em. R 1)68 2)95 3)99.7 lower value
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For Students Solutions to Odd-Numbered End-of-Chapter Exercises * Chapter 2 Review of Probability 2.1. (a) Probability distribution function for Y Outcome (number of heads) | Y 0 | Y 1 | Y 2 | Probability | 0.25 | 0.50 | 0.25 | (b) Cumulative probability distribution function for Y Outcome (number of heads) | Y 0 | 0 Y 1 | 1 Y 2 | Y 2 | Probability | 0 | 0.25 | 0.75 | 1.0 | (c) . Using Key Concept 2.3: and so that 2.3. For the two new random variables and we have:
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following figures show the histogram and the normal quantile plot (QQ plot) for the variable “Change”. Note that the sample size is small. Thus, the reliability of statistical test is dependent on the ability to assume that the data come from a normal distribution. In particular, we need to assess the normality for the variable “Change” since it is used for a statistical test. The histogram (above left) displays neither a center nor symmetry of distribution. Rather, it is bimodal, suggesting that
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PSY4807: Chapter 3: * ‘Measurement: is the transformation of psychological attributes into numbers’ * Properties of measurement scales: three key principles – magnitude – Is the measure of moreness – whether a measure is more, less of equal to another attribute. 2) Equal interval – distance between each interval is equal (6cm-8cm is the same interval as 10cm-12cm). 3) Absolute zero: nothing present of the attribute being tested. I.e 0 cm tall. Not the same for measuring intelligence,
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Research 4 2) The Marketing Research process 4 II- Body 1: Litterature Review 6 1) Inferential Statistics 6 a) Dummy Variables 7 b) Experimental Analysis 7 2) Normal Distribution 8 Figure 1: A normal Distribution, bell-shaped curve 9 3) Skewness 9 4) The Kurtosis 9 5) Formula of Kurtosis and Skewness over their Standard error 10 6) Central Limit Theorem 10 7) T Test Hypothesis testing for one sample mean 11 a) State the Null and Alternative Hypothesis 11 b) Hypothesis of the Testing
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based on the Standard & Poor (S&P) 500 Index—LARGEST 2. Small- Company Stocks: portfolios based on smallest 20% of companies on the New York Stock Exchange. 3. Long-term corporate bonds: portfolios of high-quality bonds with 20 years to maturity. 4. Long-term U.S. government bonds: portfolios of U.S. government bonds with 20 years to maturity. 5. U.S. Treasury bills: portfolio bills with a three-month maturity. (T-Bill) Consumer Price Index (CPI): a standard measure of consumer
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numbers are 86 and 86 to find the median we take the middle of those numbers which is 86. 4. Standard Deviation Group A: (26-39.5)^2= 182.25 (38-39.5)^2= 2.25 (19-39.5)^2= 420.25 (51-39.5)^2= 132.25 (58-39.5)^2= 342.25 (19-39.5) ^2= 420.25 (61-39.5)^2= 462.25 (34-39.5)^2= 30.25 (68-39.5)^2= 812.25 (21-39.5)^2= 342.25 Total= 3146.25 Standard deviation equals √3146.25/10-1= √349.61) = 18.70 Standard Deviation Group B: (24-16.8)^2= 51.84 (18-16.8)^2= 1.44 (11-16.8)^2= 33.64 (16-16.8)^2=
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