How long it takes paint to dry can have an impact on the production capacity of a business. In May 2018, Deal's Auto Body & Paint in Prescott, Arizona, invested in a paint-drying robot to speed up its process (The Daily Courier website, https://www.dcourier.com/photos/2018/may/26/984960336/). An interesting question is, "Do all paint-drying robots have the same drying time?" To test this, suppose we sample five drying times for each of different brands of paint-drying robots. The time in minutes until the paint was dry enough for a second coat to be applied was recorded. The following data were obtained. Click on the datafile logo to reference the data. DATA file Robot 1 Robot 2 Robot 3 Robot 4 128 144 133 150 137 133 143 142 135 142 137 135 124 146 136 140 141 130 131 153 At the = 0.05 level of significance, test to see whether the mean drying time is the same for each brand of robot. Compute the values identified below (to 2 decimals, if necessary). Sum of Squares, Treatment Sum of Squares, Error X Mean Squares, Treatment Mean Squares, Error Calculate the value of the test statistic (to 2 decimals). The p-value is between 0.05 and 0.10 What is your conclusion? Do not reject the assumption that the mean drying times are equal In the digital age of marketing, special care must be taken to ensure that programmatic ads appear on websites aligned with a company's strategy, culture, and ethics. For example, in 2017, Nordstrom, Amazon, and Whole Foods each faced boycotts from social media users when automated ads for these companies showed up on the Breitbart website (ChiefMarketer.com website). It is important for marketing professionals to understand a company's values and culture. The following data are from an experiment designed to investigate the perception of corporate ethical values among individuals specializing in marketing (higher scores indicate higher ethical values). Marketing Managers 6 5 4 5 6 4 a. Use a = 0.05 to test for a significant difference in perception among the three groups. Compute the values identified below (to 2 decimals, if necessary). x Sum of Squares, Treatment Marketing Research 5 5454 Advertising 6 7 6 5 6 6 Sum of Squares, Error Mean Squares, Treatment Mean Squares, Error Calculate the value of the test statistic (to 2 decimals). The p-value is less than 0.01 What is your conclusion? Conclude the mean perception scores for the three groups are not all the same b. Using = 0.05, determine where differences between the mean perception scores occur. Calculate Fisher's LSD value (to 2 decimals). Test whether there is a significant difference between the means for marketing managers (1), marketing research specialists (2), and advertising specialists (3). Absolute Value Difference (to 1 decimal) Conclusion 12 1-3 23 No significant difference Significant difference Significant difference Are there differences in airfare depending on which travel agency website you utilize? The following data were collected on travel agency websites on July 9, 2018. The following table contains the prices in U.S. dollars for a one-way ticket between the cities listed on the left for each of the three travel agency websites. Here the pairs of cities are the blocks and the treatments are the different websites. Click on the datafile logo to reference the data. DATA file Websites Flight From - To Expedia ($) TripAdvisor ($) Priceline ($) Atlanta to Seattle 176.00 166.00 175.80 New York to Los Angeles 195.00 195.00 206.20 Cleveland to Orlando Dallas to Indianapolis 77.00 149.00 76.21 72.00 149.00 148.20 Use a 0.05 to test for any significant differences in the mean price of a one-way airline ticket for the three travel agency websites. If your answer is zero, enter "0". Source SS of variation (to 2 decimals) Trip Website F crit MS F P-value df (to 2 decimals) (to 2 decimals) (to 4 decimals) (to 4 decimals) Error Total The p-value corresponding to Website is greater than 0.10 What is your conclusion? We cannot reject the null hypothesis that there is no difference in price among the three websites. A study reported in The Accounting Review examined the separate and joint effects of two levels of time pressure (low and moderate) and three levels of knowledge (naive, declarative, and procedural) on key word selection behavior in tax research. Subjects were given a tax case containing a set of facts, a tax issue, and a key word index consisting of 1336 key words. They were asked to select the key words they believed would refer them to a tax authority relevant to resolving the tax case. Prior to the experiment, a group of tax experts determined that the text contained 19 relevant key words. Subjects in the naive group had little or no declarative or procedural knowledge, subjects in the declarative group had significant declarative knowledge but little or no procedural knowledge, and subjects in the procedural group had significant declarative knowledge and procedural knowledge. Declarative knowledge consists of knowledge of both the applicable tax rules and the technical terms used to describe such rules. Procedural knowledge is knowledge of the rules that guide the tax researcher's search for relevant key words. Subjects in the low time pressure situation were told they had 25 minutes to complete the problem, an amount of time which should be "more than adequate" to complete the case; subjects in the moderate time pressure situation were told they would have "only" 11 minutes to complete the case. Suppose 25 subjects were selected for each of the six treatment combinations and the sample means for each treatment combination are as follows (standard deviations are in parentheses). Excel File: data13-33.xlsx Knowledge Low Naive 1.13 (1.12) Declarative Procedural 1.56 (1.33) 2.00 (1.54) Time Pressure Moderate 0.48 (0.80) 1.68 (1.36) 2.86 (1.80) Use the ANOVA procedure to test for any significant differences due to time pressure, knowledge, and interaction. Use a 0.05 level of significance. Assume that the total sum of squares for this experiment is 327.50. Letting Time Pressure be Factor A and Knowledge be Factor B, show the entries in the ANOVA table (to 2 decimals, if necessary). Do not round intermediate calculations. If your answer is zero, enter "0". Source of Variation Sum Degrees p-value of Squares of Freedom Mean Square F (to 4 decimals) Factor A x Factor B X x X Interaction Error Total 327.50