Consider the following statements: I. Principal Component Analysis (PCA) provide low-dimensional linear surfaces that are closest to the observations. II. The first principal component is the line in p-dimensional space that is closest to the observations. II. PCA finds a low dimension representation of a dataset that contains as much variation as possible. IV. PCA serves as a tool for data visualization. Determine which of the statements are correct. O a. Statements I, II, and IIII only O b. Statements I, II, and IV only 1. Statements II, III, and IV only O d. Statements I, II, and IV only O e. Statements I, II, II, and IV are all correct

Consider the following statements: I. Principal Component Analysis (PCA) provide low-dimensional linear surfaces that are closest to the observations. II. The first principal component is the line in p-dimensional space that is closest to the observations. II. PCA finds a low dimension representation of a dataset that contains as much variation as possible. IV. PCA serves as a tool for data visualization. Determine which of the statements are correct. O a. Statements I, II, and IIII only O b. Statements I, II, and IV only 1. Statements II, III, and IV only O d. Statements I, II, and IV only O e. Statements I, II, II, and IV are all correct

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter14: Data Mining

Section14.2: Classification Methods

Problem 11P

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a. What is a residual? b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? a. What is a residual? O A. A residual is a value that is determined exactly, without any error. O B. A residual is a point that has a strong effect on the regression equation. OC. A residual is a value of y-y, which is the difference between an observed value of y and a predicted value of y. OD. Aresidual is the amount that one variable changes when the other variable changes by exactly one unit. b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot? The regression line has the property that the of the residuals is the possible sum.
Please do not give solution in image format thanku what is the upper and lower limit answer asap
Resistors for electronic circuits are manufactured on a high-speed automated machine. The machine is set up to produce a large run of resistors of 1,000 ohms each. Use Exhibit 13.7. To set up the machine and to create a control chart to be used throughout the run, 15 samples were taken with four resistors in each sample. The complete list of samples and their measured values are as follows. Use three-sigma control limits. 1 2 3 4 5 6 7 SAMPLE NUMBER 1 2 8 9 10 11 3 4 5 12 13 6 7 14 15 8 9 10 11 12 13 14 a. Calculate the mean and range for the above samples. (Round "Mean" to 2 decimal places and "Range" to the nearest whole number.) 15 READINGS (IN OHMS) 1094 983 1026 1013 988 1014 991 1030 995 991 1023 1014 982 970 1016 986 1811 1030 1027 1826 983 1817 1004 1817 1018 995 982 994 1008 1897 978 976 1016 977 1010 987 994 981 1820 1001 1004 995 1015 1026 984 1030 978 1017 974 995 1007 988 995 970 1004 1028 1012 1019 983 990 Sample Number Mean Range
Resistors for electronic circults are manufactured on a high-speed automated machine. The machine is set up to produce a large run of resistors of 1,000 ohms each. Use Exhibit 10.13. To set up the machine and to create a control chart to be used throughout the run, 15 samples were taken with four resistors in each sample. The complete list of samples and their measured values are as follows: Use three-sigma control limits. SAMPLE NUMBER LA3A669 ELE 1 2 4 5 7 8 10 11 12 13 14 15 1 2 3 4 5 6 7 8 9 10 11 READINGS (IN OHMS) 985 1,009 1,003 1,015 1,009 1,019 1,005 1,010 995 990 1,015 1,020 1,013 Sample Number 12 13 14 15 991 996 994 1,001 989 992 986 989 1,001 1,006 1,005 992 1,006 996 997 1,019 991 981 989 999 993 988 1,013 1,002 1,005 1,007 1,006 996 991 994 982 996 a. Calculate the mean and range for the above samples. (Round "Mean" to 2 decimal places and "Range" to the nearest whole number.) Mean 986 994 1,008 998 993 1,005 1,020 996 1,007 979 989 1,011 1,003 984 992 Range
Please confirm if my answer to question 7 is correct and please answer question 8. Thanks ??
A technique for the study of interrelationships among variables, usually for the purposes of data reduction and the discovery of underlying constructs or latent dimensions is known as: a. Factor Analysis b. Structural Model Analysis c. Multiple linear regression d. Reliability Analysis
can you help me answer this questions: 1-A moving average is the average of the observations in the past few periods, where the number of terms in the average is the span. True False 2- All nominal data may be treated as ordinal data. False True 3 - Phone numbers, Social Security numbers, and zip codes are typically treated as numerical variables. True False 4 - Correlation is useful only for: a.measuring the strength of a linear relationship. b.conveying the same information in a simpler format than a scatterplot. c.measuring the strength of a nonlinear relationship. d.assessing the weakness of a linear relationship. 5 - Which of the following will give the value for the third quartile? a. QUARTILE.INC(array, 0.25) b.QUARTILE.INC(array, 0.75) c. PERCENTILE.INC(array, 0.75) d.DECILE.INC(array, 0.30) 6 - _______ sampling applies to populations that are divided into natural subsets and allocates the appropriate proportion of samples to each subset.…
There are three principal methods of primary data collection: interviews, experiments, and observations. * False O True
DEFINE: Typical descriptive research measuring tools 1. Descriptive statistics 2. Frequency table (with frequency and percent) 3. Charts (pie chart, bar chart, histogram, etc.) 4. Mean interpretation table (with the scale, its range for measurement purposes, scale description, and the mean interpretation) Typical correlational and comparative research measuring tools 1. Correlations 2. t-Test (paired samples, independent samples t-test) – for independent samples t-test, the grouping variable should be two categories only. 3. Analysis of variance (ANOVA) 4. Scales reliability test (interval or ratio scaled data) 5. Factor analysis 6. Normality test 7. Multiple regression analysis
3) The major variable is the central idea of the entire literature. Its sub-variables help specify which particular aspect of the major variable is being referred to. The indicators, on the other hand, are specific information that describes the sub-variables. Examples: Major variable: Study habits Sub-variable: Time required for studying, methods of studying, and place for studying Indicators: Employing patterned time intervals for effective studying: using mnemonics in memorizing the terms; and studying in one's ideal environment Instructions: Identify the major variables, sub-variables, and indicators of the examples of literature review. Example 3: On leadership Competencies and Management Skills (refer to the photo for the details)
8. assignment variable at which the treatment status does NOT change In Regression Discontinuity framework, the cutoff is defined as the level of the True False 9. What regression equation do we use for regression discontinuity framework? a) Y = Bo + B1 T + B2Xu+ Ei b) Y = Bo + B,T+ B2C + ei c) Y, = Bo + B, T+ B2 (Xi-C) + ei d) Y, = Bo + B1T + B2 (Xu + C) + € 10. Regression Discontinuity Design accomplices apples-to-apples comparison by comparing individuals as far from the cutoff as possible. True False