Strength of concrete: The compressive strength, in kilopascals, was measured for concrete blocks from five different batches of concrete, both three and sixEspedays after pouring. The data are as follows. Can you conclude that the mean strength after three days differs from the mean strength after six days? Let ,represent the mean strength after three days and H =H-5. Use the a= 0.10 level and the P-value method with the TI-84 Plus calculator.Block2345After 3 days13561337134413101348园After 6 days13521355135513241380Send data to ExcelPart 1 of 4(a) State the null and alternate hypotheses.H,:This hypothesis test is a (Choose one) v test.(b) Compute the P-value. Round the answer to at least four decimal places.P-value =Part 3 of 4Determine whether to reject Ho.(Choose one) ▼the null hypothesis.Part: 3 / 4Part 4 of 4(c) State a conclusion.There (Choose one) v enough evidence to conclude that the mean strength after three days differs from the meanstrength after six days.

There are two dependent samples which are after 3 days and after 6 days. We have to test whether the…

Answered: Strength of concrete: The compressive…

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 data below represents the daily high temperature (in 0F) recorded at the Mount Washington Observatory in New Hampshire for the first 15 days of February 2021. Use the given data to answer questions 1 - 8. Source: https://www.mountwashington.org 15 21 25 16 21 14 13 -1 6 -2 -6 15 16 21 22 A. What is the first quartile Q1?___________________________ B. What is the third quartile Q3?_________________________ C. Calculate the range._________________ D. A typical data value lies how far from the mean? (Hints: Consider the computed standard deviation) ________________
Number 3
J In-shop othesis test for the difference between two population proportions 02562 2600368.qx3zqy7 Jump to level 1 The manager of a coffee shop is trying to determine if drive-through customers buy fewer items than customers who come into the shop. The manager randomly samples both populations and calculates the proportion of customers in each that buy three or more items. The results of the data collected are shown below. What are the population parameters? Y Pick Drive-through Successes 27 Successes What is the level of significance? Ex: 0.12 Observations 76 Observations 41 119 0.345 p-hat_1 0.355 p-hat_2 What is the null hypothesis Ho? Pick Confidence Level 0.1429 What is the alternative hypothesis Ha? Pick p-value Should Ho be rejected or does Ho fail to be rejected? Pick What conclusion can be drawn from the data? Pick evidence exists to support the claim that drive-through customers buy fewer items than in-shop customers. 2 p W
Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are: fare-avg price of a one-way fare, in dollars dist- distance of the flight, in miles .reg fare ldist. Source Model Residual 551.391705 Total lfare SS ldist _cons 875.094374 df The OLS results suggest that 1 323.702668 120024315 4,594 MS Coef. Std. Err. 4,595 190444913 Number of obs F(1, 4594) Prob > F R-squared Adj R-squared Root MSE t P>|t| .4025646 .0077517 51.93 0.000 2.399834 .0521601 46.01 0.000 4,596 2696.98 0.0000 0.3699 0.3698 .34645 [95% Conf. Intervall .3873676 .4177617 2.297575 2.502093 a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare. a 1% increase in distance is associated with approximately a .40% increase in the price of the fare. a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare. None of the above.
Use the provided information to calculate the t statistic and critical t values.
To test whether the mean time needed to mix a batch of material is the same for machines produced by three manufacturers, the Jacobs Chemical Company obtained the following data on the time (in minutes) needed to mix the material. Manufacturer 2 18 30 15 24 28 14 22 33 18 20 29 17 a. Use these data to test whether the population mean times for mixing a batch of material differ for the three manufacturers. Use a = 0.05. Compute the values below (to 2 decimals, if necessary). Sum of Squares, Treatment Sum of Squares, Error Mean Squares, Treatment Mean Squares, Error Calculate the value of the test statistic (to 2 decimals). The p-value is Select your answer - What is your conclusion? - Select your answer - b. At the a = 0.05 level of significance, use Fisher's LSD procedure to test for the equality of the means for manufacturers 1 and 3. Calculate Fisher's LSD Value (to 2 decimals). What conclusion can you draw after carrying out this test? - Select your answer-
Type size Mean S.D. I 10 136.7 4.5 II 15 138.3 4.6 7. | find the 98% econfidence interval for the difference of mean fabric strengths for the two types using a pooled interval. Interpret your answer.
The data found below measure the amounts of greenhouse gas emissions from three types of vehicles. The measurements are in tons per year, expressed as CO2 equivalents. Use a 0.025 significance level to test the claim that the different types of vehicle have the same mean amount of greenhouse gas emissions. Based on the results, does the type of vehicle appear to affect the amount of greenhouse gas emissions? Click the icon to view the data. What are the hypotheses for this test? O A. Ho: At least one of the means is different from the others. H₁ H₁ H₂ H3 OB. Ho: H₁ H₁: H1 H₂ =H3 H₂ H3 OC. Ho: H₁ H₂ H3 H₁: At least one of the means is different from the others. O D. Ho: H₁ H₂ H3 H₁: H₁ H₂ =H3 Data Table Type A 6.2 6.2 6.5 7.4 7.1 6.1 6.9 7.3 6.9 6.7 Print C Type B 7.7 7.5 8.7 8.1 8.6 8.8 8.4 8.5 Type C 8.5 9.3 9.6 9.1 9.1 9.1 9.8 9.5 9.9 Done O X
The data found below measure the amounts of greenhouse gas emissions from three types of vehicles. The measurements are in tons per year, expressed as CO2 equivalents. Use a 0.05 significance level to test the claim that the different types of vehicle have the same mean amount of greenhouse gas emissions. Based on the results, does the type of vehicle appear to affect the amount of greenhouse gas emissions? Click the icon to view the data. What are the hypotheses for this test? OA. Ho: H₁ H₂ H3 H₁: H₁ H₂ H3 OB. Ho: H₁ H₂ =H3 H₁: At least one of the means is different from the others. O C. Ho: At least one of the means is different from the others. H₁: H₁=H₂ =H3 OD. Ho: H₁ H₂ H3 H₁: H1₁ H₂ H3 Determine the test statistic. F = (Round to two decimal places as needed.) Identify the P-value. P-value= (Round to two decimal places as needed.) What is the conclusion of the test? the null hypothesis. Conclude that the type of vehicle Data Table C Type A 6.5 6.2 6.5 6.5 5.8 7.5 6.4 6.4 6.2 6.9…
Average speed on a freeway is 80 mph. Among all vehicles 65% drive 8 miles above the speed limit of 70 mph. 34 What fraction drive within ± 5 mph from the mean speed? a 0.7327 b 0.6978 c 0.6646 d 0.6330
Calculate the correct t-statistics based on the information below. X1 = 200 X2 = 198 n1 = 17 n2 = 17 s1 = 2.45 s2 = 2.35 Let us assume that two groups of students at Tarleton are being compared on their average weights. Do you think the groups are different in terms of weight (measured in pounds)?
Consider the following table: SS DF MS ? 10 10 7 706.87 15 Among Treatments 4468.45 Error Total Step 3 of 8: Calculate the mean square among treatments. Please round your answer to two decimal places. LL F

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