For Exercises 25–34, use inductive reasoning to find a pattern for the answers. Then use the pattern to guess the result of the final calculation, and perform the operation to see if your answer is correct . 28. 1 = 1 2 1 + 2 + 1 = 2 2 1 + 2 + 3 + 2 + 1 = 3 2 ⋮ 1 + 2 + 3 + 4 + 5 + 6 + 7 + 6 + 5 + 4 + 3 + 2 + 1 = ?
For Exercises 25–34, use inductive reasoning to find a pattern for the answers. Then use the pattern to guess the result of the final calculation, and perform the operation to see if your answer is correct . 28. 1 = 1 2 1 + 2 + 1 = 2 2 1 + 2 + 3 + 2 + 1 = 3 2 ⋮ 1 + 2 + 3 + 4 + 5 + 6 + 7 + 6 + 5 + 4 + 3 + 2 + 1 = ?
Solution Summary: The author explains that inductive reasoning is the process of reasoning to a general conclusion through observations of specific cases.
For Exercises 25–34, use inductive reasoning to find a pattern for the answers. Then use the pattern to guess the result of the final calculation, and perform the operation to see if your answer is correct.
In a manufacturing process the assembly line speed (feet per minute) was thought to af-
fect the number of defective parts found during the inspection process. To test this theory,
managers devised a situation in which the same batch of parts was inspected visually at a
variety of line speeds. They collected the following data.
Line Speed
20
Number of Defective
Parts Found
21
20
19
40
***
40
15
30
16
60
14
17
a. Develop the estimated regression equation that relates line speed to the number of
defective parts found.
b. At a .05 level of significance, determine whether line speed and number of defective
parts found are related.
C. Did the estimated regression equation provide a good fit to the data?
d. Develop a 95% confidence interval to predict the mean number of defective parts for
a line speed of 50 feet per minute.
Please answer exercise 11.4.11 Stepwise
In exercise 12, the following data on x = average daily hotel room rate and y = amount
spent on entertainment (The Wall Street Journal, August 18, 2011) lead to the estimated
regression equation ŷ = 17.49 + 1.0334x. For these data SSE = 1541.4.
-
Room Rate
Entertainment
City
($)
($)
Boston
148
161
Denver
96
105
Nashville
91
101
New Orleans
110
142
Phoenix
90
100
San Diego
102
120
San Francisco
136
167
San Jose
90
140
Tampa
82
98
a.
Predict the amount spent on entertainment for a particular city that has a daily room
rate of $89.
b. Develop a 95% confidence interval for the mean amount spent on entertainment for
C.
all cities that have a daily room rate of $89.
The average room rate in Chicago is $128. Develop a 95% prediction interval for the
amount spent on entertainment in Chicago.
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, subject and related others by exploring similar questions and additional content below.
MFCS unit-1 || Part:1 || JNTU || Well formed formula || propositional calculus || truth tables; Author: Learn with Smily;https://www.youtube.com/watch?v=XV15Q4mCcHc;License: Standard YouTube License, CC-BY