5. Determine the missing factor. a) 8xy. )(2xy) b) -6x²= (3x²)( c) 15x¹z = (5x²)) d) -49a²b5 (76³) e) -12x³y³ = (3y³)) f) 30m²n³= (−5m²n)(■)

Would you be able to help answer the last 3? Those are the ones I am struggling with!

How would you do a check to this problem, using the original wording?

A researcher is interested in whether people who enjoy fine wine can actually tell the difference between a highly rated expensive wine and a good inexpensive wine. She selects several bottles of a highly rated cabernet sauvignon (a red wine) costing over $100 per bottle and several bottles of a good cabernet sauvignon costing $12. Subjects will taste a glass of wine without knowing whether it is the expensive or inexpensive wine. This is the treatment. They will then be asked to estimate how much the wine cost. This is the response variable. Outline a completely randomized design to compare the cost estimates for the two treatments. Twenty subjects are available. Group 1 Treatment 1 10 subjects expensive wine Compare Price estimate Random assignment Treatment 2 A Grouo 2 10 subjects inexpensive wine Group 1 10 subjects - expensive wine Random assignment Compare price estimates Group 2 10 subjects - inexpensive wine Treatment 1 Group 1 20 subjects expensive wine Compare Price estimate…

For numbers 24-26: Aquascaping involves growing aquatic plants and aesthetically arranging them in an aquarium like a natural landscape. Success of growing plants depends on several factors such as light condition, water pH, and carbon dioxide level. It is of interest to determine if varying concentrations of carbon dioxide (0.5 ppm, 1.2 ppm, 1.5 ppm) introduced to an aquarium will promote or deter an aquatic plants' growth. Ten aquariums with one-week old plant were set-up and randomly assigned to each treatment. Below are the R outputs with 5% level of significance. data: 0.5 Wilk-Shapiro Test for Normality data: 1.2 p-value = 0.324 p-value = 0.2534 data: 1.5 p-value = 0.6369 Bartlett test of homogeneity of variances height by carbon dioxide data: Bartlett's K-squared 4.5623, df = 2, p-value = 0.1022 Analysis of Variance Df Sum Sq Mean Sq F value Pr (>F) carbon dioxide 2 88.73 44.37 6.131 0.0289 * Residuals 7 50.65 7.24 . Signif. codes: 0 ***** 0.001 **** 0.01 0.05 ¹.¹ 0.1 ¹ ¹ 1…

How did you find the 1.6 in the first part of the problem?

A researcher believed that the number of rental cars in service by a car rental company would have an impact on the total annual revenue for that car rental company. Five small car rental companies were surveyed, with the number of Cars in service recorded in units of 1000 (so if a car rental company had 54000 cars in service, a 54 would be recorded) and Annual Revenue measured in millions of dollars (so an Annual Revenue of $10,000,000 would be recorded as 10). The data follows: Cars (1,000s)       Annual Revenue ($ millions)11.5                   118 10.0                   135 9.0                     100 5.5                     37 3.3                     32 Part of the Excel-generated Simple Linear Regression output is provided below: ANOVA   df SS MS F Significance F Regression 1 7891.863897 7891.863897 22.91180151 0.017339231 Residual 3 1033.336103 344.4453677     Total 4 8925.2           Coefficients Standard Error t Stat P-value Intercept -19.12490108 23.1658578…

Question 1 y -3 2 -5 -4 -3 -2 -1 -1 3 -2 -3 4.

both sheets are for the same problem.