In an effort to inform political leaders and economists discussing the deregulation of electric and gas utilities, data on eight numerical variables from utility companies have been grouped usinghierarchical clustering based on Euclidean distance to measure dissimilarity between observations and complete linkage as the agglomeration method.(a) Based on the following dendrogram, what is the most appropriate number of clusters to organize these utility companies?Distance6.56.05.55.04.5 ---4.03.53.02.52.01.51.00.50Between-Cluster Distance2.57710 13 4 20 2 21 5 1 18 14 19 6 3 9 7 12 15 17 8 16 11Clusterclusters are appropriate based on complete linkage.(b) Using the following data on the Observations 10, 13, 4, and 20, confirm that the complete linkage distance between the cluster containing (10, 13) and the cluster containing {4, 20} is 2.577units as displayed in the dendrogram. (b) Using the following data on the Observations 10, 13, 4, and 20, confirm that the complete linkage distance between the cluster containing {10, 13) and the cluster containing {4, 20} is 2.577units as displayed in the dendrogram.Income/DebtReturnCostLoadPeakSalesPercentNuclearTotal FuelCostsObservation100.0320.7410.700-0.892-0.173-0.6931.620-0.863130.1950.8750.748-0.7351.013-0.4892.275-1.0354-0.5100.207-0.004-0.219-0.943-0.7021.328-0.724Distance from Observation 10 and Observation 4:Distance from Observation 10 and Observation 20:Distance from Observation 13 and Observation 4:Distance from Observation 13 and Observation 20:200.4660.474-0.4900.6550.083-0.4581.733-0.721If required, round your answers to three decimal places. Do not round intermediate calculations.Based on complete linkage, the merger of cluster (10, 13) and cluster {4, 20} is Select your answer -of these four distances. Thus, the increase in within-clusterdissimilarity of the new merged cluster - Select your answer based on the distance between Observation 13 and Observation 4.

The objective is to identify the number of clusters to organize the utility companies based on…

Answered: In an effort to inform political…

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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The business objective of the director of Game Ghana is to forecast monthly sales for all new stores, based on the number of profiled customers who live no more than 30 minutes from a Game store. To examine the relationship between the number of profiled customers who live within a fixed radius from a Game store and it monthly sales, data were collected from a sample of 10 stores:Store 1 2 3 4 5 6 7 8 9 10No of customers (‘000)5728432453 Monthly Sales (‘000)81261487910128(a) Use the least-squares method to compute the regression coefficients ? ??? ?(b) Write down the estimated equation and predict the monthly sales if there are 9000 customers(c) Determine the coefficient of determination, r2 and explain its meaning in this problem(d) Determine the value of the extent of relationship between monthly sales and number of customers, and interpret your results.
Mendel counted 4000 peas from a dihybrid cross and predicted a 9:3:3:1 phenotypic ratio with the following results. Yellow and smooth peas 2100; yellow and wrinkled peas 700: green and smooth peas 859 and green and wrinkled peas 341. Support or refute these data with a CHI-Square analysis. State the Null hypothesis and its outcome for this set of data.
In a medical study on the maximum heart rates of cardiac patients in a two-minute stress test, two groups had the following summary statistics.Group A: median = 145 beats/min, interquartile range = 9.0 beats/minGroup B: median = 148.5 beats/min, interquartile range = 10.0 beats/minWhich comparison is correct? 1 Members of Group A had slower heartbeats and less variation than Group B. 2 Members of Group A had slower heartbeats and more variation than Group B. 3 Members of Group A had faster heartbeats and more variation than Group B. 4 Members of Group A had faster heartbeats and less variation than Group B.
A statistical program is recommended. Jensen Tire & Auto is in the process of deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine. Managers feel that maintenance expense should be related to usage, and they collected the following information on weekly usage (hours) and annual maintenance expense (in hundreds of dollars). Weekly Usage(hours) AnnualMaintenanceExpense 13 17.0 10 22.0 20 30.0 28 37.0 32 47.0 17 30.5 24 32.5 31 39.0 40 51.5 38 40.0 #1) Develop the estimated regression equation that could be used to predict the annual maintenance expense (in hundreds of dollars) given the weekly usage (in hours). (Round your numerical values to two decimal places.) #2) The expected expense of a machine being used 34 hours per week is $ hundred.
A researcher notes that there seems to be a difference in the prevalence of individuals who are medication adherent and have high levels of education along with a high health literacy and the prevalence of individuals who are not medication adherent and have low levels of education along with a low health literacy. Use the appropriate hypothesis to determine if education level and health literacy status are related (independent) at the 5%. Low Level of Education Low Medication Adherence High Medication Adherence Total Low Health Literacy 91 9 100 High Health Literacy 9 291 300 Total 100 300 400 High Level of Education Low Medication Adherence High Medication Adherence Total Low Health Literacy 96 4 100 High Health Literacy 4 296 300 Total 100 300 400
A Deputy Registrar at a certainty university conducted a Chi-Square test of association to establish whether or not employee grade and level of absenteeism were associated. Table 2 below shows part of the results which were obtained. Table 2: Cross tabulation of employee grade and level of absenteeism Contingency Tables Grade LAbsence 1 2 3 Total low Observed 8 1 0 9 Expected 2.90 3.48 2.61 9.00 high Observed 2 11 9 22 Expected 7.10 8.52 6.39 22.00 Total Observed 10 12 9 31 Expected 10.00 12.00 9.00 31.00 2.1 State the appropriate measurement scales for the variables. 2.2 State the null and alternative hypotheses. 2.3 Calculate the expected frequency corresponding to a Grade 3 academic with a high level of absenteeism. 2.4 Find the Chi-Square critical value and test statistic.…
A Deputy Registrar at a certainty university conducted a Chi-Square test of association to establish whether or not employee grade and level of absenteeism were associated. Table 2 below shows part of the results which were obtained. Table 2: Cross tabulation of employee grade and level of absenteeism Contingency Tables Grade LAbsence 1 2 3 Total low Observed 8 1 0 9 Expected 2.90 3.48 2.61 9.00 high Observed 2 11 9 22 Expected 7.10 8.52 6.39 22.00 Total Observed 10 12 9 31 Expected 10.00 12.00 9.00 31.00 2.2 State the null and alternative hypotheses.
A Deputy Registrar at a certainty university conducted a Chi-Square test of association to establish whether or not employee grade and level of absenteeism were associated. Table 2 below shows part of the results which were obtained. Table 2: Cross tabulation of employee grade and level of absenteeism Contingency Tables Grade LAbsence 1 2 3 Total low Observed 8 1 0 9 Expected 2.90 3.48 2.61 9.00 high Observed 2 11 9 22 Expected 7.10 8.52 6.39 22.00 Total Observed 10 12 9 31 Expected 10.00 12.00 9.00 31.00 2.3 Calculate the expected frequency corresponding to a Grade 3 academic with a high level of absenteeism.
A Deputy Registrar at a certainty university conducted a Chi-Square test of association to establish whether or not employee grade and level of absenteeism were associated. Table 2 below shows part of the results which were obtained. Table 2: Cross tabulation of employee grade and level of absenteeism Contingency Tables Grade LAbsence 1 2 3 Total low Observed 8 1 0 9 Expected 2.90 3.48 2.61 9.00 high Observed 2 11 9 22 Expected 7.10 8.52 6.39 22.00 Total Observed 10 12 9 31 Expected 10.00 12.00 9.00 31.00 2.4 Find the Chi-Square critical value and test statistic. Hence, conduct a Chi-Square test of association at 5% level of significance clearly stating your decision and conclusion.
A Deputy Registrar at a certainty university conducted a Chi-Square test of association to establish whether or not employee grade and level of absenteeism were associated. Table 2 below shows part of the results which were obtained. Table 2: Cross tabulation of employee grade and level of absenteeism Contingency Tables Grade LAbsence 1 2 3 Total low Observed 8 1 0 9 Expected 2.90 3.48 2.61 9.00 high Observed 2 11 9 22 Expected 7.10 8.52 6.39 22.00 Total Observed 10 12 9 31 Expected 10.00 12.00 9.00 31.00 2.1 State the appropriate measurement scales for the variables.
1) A cement producer, manufactures and then fills 40kg-bags of powder cement on twodistinct production tracks located in separate suburbs. To determine whether differencesexist between the average fill rates for the two tracks, a random sample of 25 bags fromTrack 1 and a random sample of 16 bags from Track 2 were recently selected. Each bag’sweight was measured and the following information measures from the samples arereported:Production ProductionTrack 1 Track 2n1 = 25 n2 = 16x2 = 40.02 x1 = 39.87 s1 = 0.59 s2 = 0.88 Supervision believes that the fill rates of the two tracks are normally distributed with equalvariances.Construct a 95% confidence interval estimate of the true mean difference between the twotracks.--------------------------------------------------------------------------------------------------------------2) Two independent simple random samples were selected from two normallydistributed populations with unequal variances yielded the following information:Sample 1…
A sociologist wants to investigate the question, "Is there a relationship between texting during class and grade-point-average (GPA) among high school seniors in a large district?" Which study design is most appropriate? Before the semester starts, randomly select 40 seniors from each high school who do not text during class. Assign 20 to the texting treatment group (text three or more times during every class meeting) and 20 to the control group (no texting during class). At the end of the semester, obtain each student’s GPA from the appropriate admissions and records office. Compare the GPA of students who routinely text during class to the GPA of students who do not text during class. Before the semester starts, randomly select 40 seniors from each high school who do not text during class. Assign 20 to the texting treatment group (text three or more times during every class meeting) and 20 to the control group (no texting during class). At the end of the semester,…

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