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Text message users receive or send an average of 41.5

/in /by

Get college assignment help at Smashing Essays Question Text message users receive or send an average of 41.5 text messages per day.a) How many text messages does a text message user receive or send per hour?b) What is the probability that a text message user receives or sends two messages per hour?c) What is the probability that a text message user receives or sends more than two messages per hour?X= 41.5/24≈1.7292X∼P(1.7292)P(x=2)=poissonpdf(1.7292,2)≈0.2653P(x>2)=1-P(x≤2)=1-poissoncdf(1.7292,2)≈1-0.7495=0.2505PLEASE explain how to compute the poissonpdf and poissoncdf in the above question. How it end up in the final answers? Thanks

The owner of a moving company wishes to predict the

Question The owner of a moving company wishes to predict the number of man hours that will be required for prospective moves. The variables he will use to predict the number of man hours needed are:X1 – The number of cubic feet of goods movedX2 – The number of large pieces to be movedX3 – A dummy variable that is equal to 1 if there is a freight elevator available; 0 otherwise.The output from the regression analysis used to estimate this equation is given below:1.What proportion of the variation in hours is explained by the regression if we ignore the impact of the sample size and the number of predictor variables? Include 3 decimal places in your answer.2.What proportion of the variation in hours is explained by the regression if we take into account the impact of the sample size and the number of predictor variables? Include 3 decimal places in your answer.3.What is the value of the test statistic used to evaluate the following null hypothesis?H0: β1 = β2 = β3 = 0Include 2 decimal places in your answer.4.What is the standard deviation of Y – the number of man hours required? Include 1 decimal place in your answer.5.How many man hours are predicted for a move that include 900 cubic feet of goods, five large pieces, and does not have a freight elevator? Round your answer to 1 decimal place6.What is the value of the test statistic used in determining if the number of large pieces being moved is a useful predictor of the number of man hours required? Include 2 decimal places in your answer. ATTACHMENT PREVIEW Download attachment Moving.png SUMMARY OUTPUT Regression Statistics Multiple R 0.981 R Square 0.962 Adjusted R Square 0.958 Standard Error 3.056 Observations 36 ANOVA SS MS F Significance F Regression 3 7472.6 2490.9 266.76 1.03383E-22 Residua 32 298.8 9.3 Total 35 7771.4375 Coefficients | Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.990 1.908 1.57 0.126846423 0.896 5.877 0.896 6.877 Feet 0.026 0.004 6.80 1.09007E-07 0.018 0.033 0.018 0.033 Large 5.042 0.722 6.99 6.43027E-08 3.573 6.512 3.573 6.512 Elevator .6.768 1.382 -4.90 2.67838E-05 -9.583 -3.953 -9.583 -3.953Read more

asks for variance probability. ATTACHMENT PREVIEW Download attachment exercise 5.7.1.PNG

Question asks for variance probability. ATTACHMENT PREVIEW Download attachment exercise 5.7.1.PNG

how distiguish between an independent and dependent variable?

Question how distiguish between an independent and dependent variable?

Bicycling World, a magazine devoted to cycling, reviews hundreds of

Question Bicycling World, a magazine devoted to cycling, reviews hundreds of bicycles throughout the year. Its “Road-Race” category contains reviews of bicycles used by riders primarily interested in racing. One of the most important factors in selecting a bicycle for racing the weight of the bicycle. The following data show the weight (pounds) and price ($) for ten racing bicycles reviewed by the magazine.(b) Use the data to develop an estimated regression equation that could be used to estimate the price for a bicycle given its weight. What is the estimated regression model? Let x represent the bicycle weight. If required, round your answers to two decimal places. For subtractive or negative numbers use a minus sign even if there is a sign before the blank. (Example: -300) =   xI got28818.00368-1439.00644 

Using Excel, show the correct functions to solve T test

Question Using Excel, show the correct functions to solve T test equation. src=”/qa/attachment/8997997/” alt=”T test.png” /> ATTACHMENT PREVIEW Download attachment T test.png Week # Weekly Weekly Sales($) Sales($) – Rep A – Rep B 4700 5900 6100 2600 3438 2845 7394 4763 You want to determine whether there is a statistically different 4350 3740 Hypothesis test format average weekly 2552 2315 sales between Sales Rep A and Sales Rep B. 7063 1599 7844 1629 Step | State Hypothesis 6898 2416 Ho Create Null and Alternative Hypothesis statements that would allow 4003 2107 Ha you 6884 4237 12 4007 6322 to determine whether or not their sales performance is statistically Step II Choose significance level (alpha) 13 7214 3725 a= different. 14 2358 5890 15 7745 5119 16 Step III Calculate test statistic and p value 1337 5184 Use a significance level of .05 to conduct a t-test of independent 1052 3439 samples 17 Step IV Decision Rule 18 6052 4828 Reject Ho if p value

Most scientists use the p<.05 criterion to determine if their

Question Most scientists use the p<.05 criterion to determine if their findings are significant. Describe cases where you would prefer them to be more lenient (e.g., p<.10) or cases where you prefer them to be more cautious (e.g., p<.01).

/>Hello, could you assist with this question? Attachment 1 Attachment

Question />Hello, could you assist with this question? Attachment 1 Attachment 2 ATTACHMENT PREVIEW Download attachment no.3 con’t.png ATTACHMENT PREVIEW Download attachment no.3.png (3) Let the conditional probability density of X , given A to be Poisson in other words: B—AAJ: — = 0 1 2 A = z! 17 7 7 3 “ml ) { 0 otherwise } Also, let A (the intensity rate of the Poisson distribution) to follow a Gamma distribu- tion with two parameters a and ,8. In other words, we have the following: (A) _ SELF—15m (A and Cl! and fl)

Can you help me with the following problems? Questions 1-4.

Question Can you help me with the following problems? Questions 1-4. A dog allergy test for people has a 90% accuracy rate. Only 1% of the population has an allergy to dogs (actually it is much smaller than that!). Assume a major pet food manufacturer purchases this test and administers it to 1,000 employees. 1. Fill out the table below.  Test Shows Positive Test Shows Negative Total Has Allergy   Not Allergic   Total   2. If an employee has a dog allergy, what is the probability he/she will test positive? (enter the answer as a percent rounded to the nearest tenth as needed) 3. If an employee tested positive, what is the probability he/she has a dog allergy? (enter the answer as a percent rounded to the nearest tenth as needed) 4. If an employee tested negative, what is the probability he/she has a dog allergy? (enter the answer as a percent rounded to the nearest tenth as needed)

Can you help me with the following problem”Questions 5-7. Suppose

Question Can you help me with the following problem”Questions 5-7. Suppose .01% of the residents of a city with 1 million people are terrorists. The city buys facial recognition software that can identify these terrorists with 99% accuracy. 5. Fill out the table below.  Test Shows Positive Test Shows Negative Total Terrorist   Not a Terrorist   Total   6. If the police receive a ‘hit’ on a recognized face, what is the probability that it was a false positive? (enter the answer as a percent rounded to the nearest tenth as needed) 7. If you are a terrorist, what is the probability that the software will recognize you? (enter the answer as a percent rounded to the nearest tenth as needed) 8. Determine if the following is an example of a false negative or an example of a false positive.               A woman does not have breast cancer. Her test indicates that she has breast cancer. This is an example of a _____________.

Please help me with the following problem.Officials administer a drug

Get college assignment help at Smashing Essays Question Please help me with the following problem.Officials administer a drug test to 500 athletes to determine if they are using performance-enhancing drugs (PEDs). A positive result indicates that the athlete is using performanceenhancing drugs; a negative result indicates that the athlete is not using these drugs. However, this test is not 100% accurate, so some errors occur. The following table shows the results for a group of athletes. Athlete PED Use   Athletes using PEDs Athletes not using PEDs Total Positive Test Result             87                 5   92Negative Test Result             15                393 408 Total            102               398 500 9. What is the chance that a positive result is a false positive? (Enter answer as a percent. Round to the nearest tenth as needed) 10. Imagine yourself as an official interpreting the results of the test. What actions might you take against an athlete who receives a positive result? 11. An athlete is not using PEDs. What is the chance that his or her test will return a negative result? 12. What is the chance that a negative test result is a false negative? (Enter answer as a percent. Round to the nearest tenth as needed)

HELP MAT 300

Question HELP MAT 300

This question was created from Chau Tran HW11 MGMT650_Summer2019.xlsx https://www.coursehero.com/file/44099772/Chau-Tran-HW11-MGMT650-Summer2019xlsx/

Question This question was created from Chau Tran HW11 MGMT650_Summer2019.xlsx https://www..com/file/44099772/Chau-Tran-HW11-MGMT650-Summer2019xlsx/ Find the Expected values for each of the colors. Saeko expects that the colors sell in equal amounts. Color Type Sum of Yards Black 19762.00 White 17649.00 Primary Colors 20550.00 Tertiary Colors 21803.00 Total 79764.00 ATTACHMENT PREVIEW Download attachment 44099772-332519.jpeg Using the pivot table that you just created, I’ll in the blanks in the following table: Primary Colors consists of the sum of Blue, Red, and Yellow yarn sold Tertiary Colors consists of the sum of Brown, Green, and Purple Colors Sold The Total in this chart must equal the Grand Total, Cell 018 in the shove table. Color Type Sum of Yards White Primary Colors Tertiary Colors Total This table represents the observed data in the Chi Square analysis. Find the Expected values for each of the colors. Sacks expects that the colors sell in equ Color Type Sum of Yards Black White Primary Colors Tertiary Colors Total Subtract the Expected valves from the observed values Color Type Sum of Yards Black White Primary Colors Tertiary Colors

I need the R codes as well. /> Attachment 1

Question I need the R codes as well. /> Attachment 1 Attachment 2 Attachment 3 ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.27.15.png Does pollution have effect on mortality? Data in one early study designed to explore this issue came fi‘om 60 Standard Metropolitan Statistical Area (SMSA) in the United States, obtained for the years 1959-1961. [Source: GC McDonald and J S Ayers, “Some applications of the ‘Chemoff Faces’: a technique for graphically representing multivariate data”, in Graphical Representation of Multivariate Data, Academic Press, 1978. Total age-adjusted mortality [MORT] from all causes, in deaths per 100,000 population, is the response variable. The predictor variables are listed below: Mean annual precipitation (in inches) [PRECIP], Median number of school years completed by persons of age 25 or over [EDUC], Percentage of population in 1960 that is nonwhite [NONWHITE], Percentage of households with annual income under $3000 in 1960 [POOR], Relative pollution potential of oxides of nitrogen (N OX) [NOX], Relative pollution potential of sulphur dioxide (S02) [802]. [“Relative pollution potential” is the product of the tons emitted per day per square kilometer and a factor correcting for SMSA dimension and exposure] The goal of the analysis would be to relate mortality to all the variables. Thus mortality is the response variable. It would be also important to see if pollution is related to mortality. Since the variables NOX and SO; are skewed, it will be a good idea to transform them by using the natural logarithm. Also the variables NONWHITE and POOR are skewed, and it may be reasonable to transform them using a cube root. ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.27.26.png Analyze the data set given below using the regression method after transforming the variables. Perform a complete analysis including residual analysis, variable selection etc. Prepare a thorough report as you would do for a client. This report should include all the steps used in the analysis, their justifications (relevant plots, analysis of residuals, diagnostics etc.), and your conclusions. Also comment on the possible improvements that can be made on your analysis if you detect nonlinearities, unequal variance, outliers etc. Please cut and paste the relevant portions from your computer printouts. Please attach your R codes in an appendix of your report. You may want to follow the steps given below with a summary of your findings for each step. 1. There should be an introduction with a brief description of the data and goal of the analysis. ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.27.37.png 2. Obtain a matrix plot of the data, calculate the correlation matrix, fit the regression, obtain the AN OVA table, estimates of the parameters and their standard errors etc. 3. Do the diagnostics: plot the observed Y values against the fitted Y-values, plot the residuals against the independent variables, histogram of residuals, normal probability plot of residuals etc. 4. If you believe there is some nonlinearity in the data from your analysis in steps 2 and 3, then include the nonlinear terms (such as squares), fit the regression, obtain the ANOVA table, estimates of the parameters along with their standard errors, plot of observed against fitted Y values, plot of residuals against the fitted values, histogram of residuals, normal probability plot etc. [There may be no need to do Box-Cox transformations if you begin the data analysis after transforming the variables as suggested] 5. If you believe some variables can be deleted from your model (either from step (2) if you do not suspect nonlinearity or the model fiom step (4) if you suspect nonlinearity), then use all subsets regression (if possible using the computer) and stepwise procedures for model selection. If you have used both procedures (all subsets and stepwise), then comment on the differences between the results, if any. 6. Summarize your findings. Briefly discuss if further analysis is needed for this data. 7. Attach all the R codes in an Appendix of the report. Format – Reports should be typed. – The report should include a title page. – The main body of the report should contain no R code. – All R code should be included in an appendix. – A hard copy of the report must be submitted.

Please give me a step by step break down of

Question Please give me a step by step break down of how you would solve this: alt=”Screen Shot 2019-08-01 at 9.34.38 PM.png” /> ATTACHMENT PREVIEW Download attachment Screen Shot 2019-08-01 at 9.34.38 PM.png A researcher wishes to determine if a particular drug affects pilot reaction time to air traffic controller instructions. The researcher has 10 pilots. The pilots are observed in normal performance and their reaction times are recorded. Then the pilots are administered the drug, observed again, and their reaction times are recorded. The expectation is that the drug will reduce reaction time. Pilot Trial 1 Time (sec) Trail 2 Time (sec) A 83 69 B 74 71 C .82 .79 D 86 .87 E 66 65 F 63 .68 G 81 67 H 77 .72 73 .71 69 65 Conduct a t test using the five-step hypothesis testing process and StatCrunch,

I can send you the data file. btw how to

Question I can send you the data file. btw how to change the price? alt=”Screenshot 2019-08-01 19.27.15.png” /> Attachment 1 Attachment 2 Attachment 3 Attachment 4 Attachment 5 ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.27.15.png Does pollution have effect on mortality? Data in one early study designed to explore this issue came fi‘om 60 Standard Metropolitan Statistical Area (SMSA) in the United States, obtained for the years 1959-1961. [Source: GC McDonald and J S Ayers, “Some applications of the ‘Chemoff Faces’: a technique for graphically representing multivariate data”, in Graphical Representation of Multivariate Data, Academic Press, 1978. Total age-adjusted mortality [MORT] from all causes, in deaths per 100,000 population, is the response variable. The predictor variables are listed below: Mean annual precipitation (in inches) [PRECIP], Median number of school years completed by persons of age 25 or over [EDUC], Percentage of population in 1960 that is nonwhite [NONWHITE], Percentage of households with annual income under $3000 in 1960 [POOR], Relative pollution potential of oxides of nitrogen (N OX) [NOX], Relative pollution potential of sulphur dioxide (S02) [802]. [“Relative pollution potential” is the product of the tons emitted per day per square kilometer and a factor correcting for SMSA dimension and exposure] The goal of the analysis would be to relate mortality to all the variables. Thus mortality is the response variable. It would be also important to see if pollution is related to mortality. Since the variables NOX and SO; are skewed, it will be a good idea to transform them by using the natural logarithm. Also the variables NONWHITE and POOR are skewed, and it may be reasonable to transform them using a cube root. ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.27.26.png Analyze the data set given below using the regression method after transforming the variables. Perform a complete analysis including residual analysis, variable selection etc. Prepare a thorough report as you would do for a client. This report should include all the steps used in the analysis, their justifications (relevant plots, analysis of residuals, diagnostics etc.), and your conclusions. Also comment on the possible improvements that can be made on your analysis if you detect nonlinearities, unequal variance, outliers etc. Please cut and paste the relevant portions from your computer printouts. Please attach your R codes in an appendix of your report. You may want to follow the steps given below with a summary of your findings for each step. 1. There should be an introduction with a brief description of the data and goal of the analysis. ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.48.41.png ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.48.55.png ATTACHMENT PREVIEW Download attachment Screenshot 2019-08-01 19.50.31.png 2. Obtain a matrix plot of the data, calculate the correlation matrix, fit the regression, obtain the ANOVA table, estimates of the parameters and their standard errors etc. 3. Do the diagnostics: plot the observed Y values against the fitted Y-values, plot the residuals against the independent variables, histogram of residuals, normal probability plot of residuals etc. 4. If you believe there is some nonlinearity in the data from your analysis in steps 2 and 3, then include the nonlinear terms (such as squares), fit the regression, obtain the ANOVA table, estimates of the parameters along with their standard errors, plot of observed against fitted Y values, plot of residuals against the fitted values, histogram of residuals, normal probability plot etc. [There may be no need to do Box-Cox transformations if you begin the data analysis after transforming the variables as suggested] 5. If you believe some variables can be deleted from your model (either from step (2) if you do not suspect nonlinearity or the model from step (4) if you suspect nonlinearity), then use all subsets regression (if possible using the computer) and stepwise procedures for model selection. If you have used both procedures (all subsets and stepwise), then comment on the differences between the results, if any. 6. Summarize your findings. Briefly discuss if further analysis is needed for this data. 7. Attach all the R codes in an Appendix of the report. Format – Reports should be typed. – The report should include a title page. – The main body of the report should contain no R code. – All R code should be included in an appendix.

The attachment is above please help!! ATTACHMENT PREVIEW Download attachment

Question The attachment is above please help!! ATTACHMENT PREVIEW Download attachment Screen Shot 2019-08-01 at 9.09.52 PM.png Determine pi and ”i from the given parameters of the population and sample size. p=32.a=17,n=33 Hf 61-:- (Rnund to three decimal places as needed.)

a. Attributable risk percentage b. Incidence proportion ratio c. Positive

Question a. Attributable risk percentage b. Incidence proportion ratio c. Positive predictive value d. Odds ratio

Please help me!!! attachment below ATTACHMENT PREVIEW Download attachment Screen

Question Please help me!!! attachment below ATTACHMENT PREVIEW Download attachment Screen Shot 2019-08-01 at 9.12.14 PM.png Describe the sampling distribution of p. Assume the size of the population is 15,000. n = 700, p =0.7 Choose the phrase that best describes the shape of the sampling distribution of p below. O A. Approximately normal because n $ 0.05N and np(1 – p) 2 10. O B. Not normal because n $ 0.05N and np(1 – p)

For this Assignment, review the following:Using AWE Level 4000 writing guidelines submit

For this Assignment, review the following:Using AWE Level 4000 writing guidelines submit a 3- to 4-page paper (not including the title page, reference list, and appraisal guides) on your EBP project including:Pay specific attention to the Writing Expectations 4000 Checklist. Paraphrase, avoid direct quotes, and use your own words supported by evidence to exhibit scholarly writing. Do not use articles older than 5 years unless they have been confirmed as seminal articles by your Instructor. At least 5 sources of evidence are required for your paper. Attach appraisals after the reference page for each article used. (See the Clinical Guideline Appraisal and Systematic Review Appraisal in this week’s Resources.)

An epidemiological study is set up to examine the association

Question An epidemiological study is set up to examine the association between bronchitis and air pollution. The investigator wants to find out whether the prevalence of bronchitis is higher among those exposed to air pollution, according to measurements in their environment, than among people not exposed to air pollution. Such a study is an example of a(n)…  a. Cohort study   b. Ecological study   c. Cross-sectional study   d. Case-control study  

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