;a) Explain why and how the following measures and test statistics are used when conducting7. (-factor analysis.i) Cronbach's Alpha ii) Kaiser-Meyer-Olkin (KMO) Test ii) Barrlett's Testb) How are eigenvalues used when interpreting the variance explained table in factor analysis.c) How do you use the factor-loading matrix to interpret the meaning of factors in factor analysis?d) How would you evaluate the reliability and validity of the factor analysis?

Factors: Linear combination (variate) of the original variables. Factors represent the underlying…

Answered: 7. (- factor analysis. :a) Explain why…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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b. A best-fit line has been included on the calibration curve via a least squares analysis. By simple visual inspection of the figure to the right (do not re-create it), explicitly write out the equation/model for this calibration curve including units. c. Using your model (i.e. not just visual) from part-b of this question, what would be the analyte concentration when the detector response is 250 mV (show your work)?d. Using your model from part-b and extrapolating, what would be measured detector response when the concentration is 73.7 uM? (show your work)?
A data set is given below. (a) Draw a scatter diagram. Comment on the type of relation that appears to exist between x and y (b) Given that x =3.5000, s, = 2.2583, y = 4.4667, s, = 1.7682, and r= -0.9416, determine the least-squares regression line. (c) Graph the least-squares regression line on the scatter diagram drawn in part (a). 6 3 4 5.4 68 5.6 4.0 2.3 2.7 1 y (a) Choose the correct graph below. O A Oc. Q There appears to be V relationship (b) y=+ O (Round to three decimal places as needed.) (c) Choose the correct graph below. O A OB. OC. OD.
You are conducting a test of independence for the daim that there is an association between the row variable and the column variable. Red Blue Green Male 23 35 25 Female 23 13 60 What is the chi-square test-statistic and the corresponding p-value for this data? x² - [three decimal accuracy] p-value [three decimal accuracy]
Test whether there is a significant interaction effect between noise (Factor A) and gender (Factor B) at a 5% significance.
2. Consider the foot length and foot width of six female grade 4 students in Morning Star Montessori School in 2006: Length of foot (cm) Y 20.9 Width of foot (cm) X 8.5 24 9 19.6 7.9 22.6 8.8 21 8.8 21.6 9.3 c) What is the least squares regression line for Y as a function of X?
Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST-10,850; SSTR-4,570 a. Set up the ANOVA table for this problem (to 2 decimals, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value (to 4 decimals) Treatments Error Total buse a 05 to test for any significant difference in the means for the three assembly methods. Calculate the value of the test statistic (to 2 decimals) The p-value is Select your answer What is your conclusion -Select your answer bep < (A₁ 3
4
Goals scored by two Football teams, France and Argentina, in last 5 years international matches are mentioned in the following Table 1: Number of Goals in match Number of Matches of FRANCE Number of matches of ARGENTINA 0 26 20 1 18 17 2 10 12 3 08 09 4 06 08 5 05 06 Table 1 Estimate the Coefficient of Variation of both teams. According to the results of (a), which team is more consistent?
Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 42 employees were randomily selected and randomly assigned to the three proposed methods in such a way that each method was used by 14 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST - 14,150; SSTR - 4,510. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two dedimal places, and your p-value to four decimal places.) Source Sum Degrees Mean p-value of Variation of Squares of Freedom Square 4510 2 2256 6.00 0.0056 Treatments 10000 27 37037 Error 14510 29 Total (b) Use a - 0.05 to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. O Ha: Not all the population means are equal. O H: At least two…
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An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction, Use a = ,05. Factor A is method of loading and unloading; Factor B is the type of ride. Type of Ride Roller Coaster Screaming Demon Long Flume Method 1 48 56 51 50 48 47 Method 2 51 55 52 53 51 48 a. Set up the ANOVA table (to 2 decimal, if necessary). Round p-value to four decimal places. Source of Variation Sum of Squares Degrees of Freedom Mean Square p-value Factor A Factor B Interaction Error Total
An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use a=0.05 . Factor A is method of loading and unloading; Factor B is the type of ride. Type of Ride Roller Coaster Screaming Demon Long Flume Method 1 47 51 54 49 43 50 Method 2 51 47 50 53 43 46 Set up the ANOVA table (to whole number, but -value to 2 decimals and value to 1 decimal, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square F -value Factor A Factor B Interaction…

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