Three different methods for assembling a product were proposed by an Industrial engineer. To Investigate the number of units assembled correctly with each method, 36 employees were randomly selected and randomly assigned to the three proposed methods In such a way that each method was used by 12 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: SST = 12,750; SSTR = 4,510. (a) Set up the ANOVA table for this problem. (Round your values for MSE and F to two decimal places, and your p-value to four decimal places.) Source of Varlation Degrees of Freedom Mean Square Sum of Squares F p-value Treatments Error Total (b) Use a- 0.ós to test for any significant difference in the means for the three assembly methods. State the null and alternative hypotheses. O Ho: H H2 H O Ho: At least two of the population means are equal. H At least two of the population means are different. H Not all the population means are equal. O Ho: Not all the population means are equal. Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to four decimal places.) p-value-
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Trending now
This is a popular solution!
Step by step
Solved in 2 steps with 7 images