Kaplan University, Davenport IA GB 513 Quiz

********* ********* ** *** ********* ******* * *** * ******

******* * 2)

****** ******** correlation

********* ** correlation

strong ******** correlation

******** negative ************

**** negative ************

******** ** * cost accountant ** developing a ********** ***** to ******* *** ***** **** ** ********* * ***** ** printed circuit ****** ** a function ** ***** **** (the ****** ** boards ******** ** *** lot ** ****** The *********** ******** *** ******* * ***

***** *****

**** ******** *****

***** cost

***** *****

total ******** cost

Question 33 * **** accountant ** ********** a ********** model ** ******* the ***** **** ** ********* * ***** of ******* ******* boards ** a linear ******** ** ***** **** **** ****** of ****** ******** ** one *** ** ****** *** ********* ** **** model is **** ******* : ***

batch *****

**** ******** *****

***** *****

***** cost

***** variable cost

Question ** ** * *** * ** * ********** ***** are ******* ********** (Points * ***

the *********** coefficient ***** ** ***

*** *********** ** ************* ***** ** the

coefficient ** determination would ** 1
***

*** would ** *** ***

***** ** *** Question 55

* ******* wishes to predict *** ****** **** *** ** ** ********** ***** ** *** ****** of ***** *** driven *** following ***** *** developed: * = **** * ***** ** *

car ** ****** ***** ***** the predicted cost *** ******* * *** 2090
3850

*****

*****

*****

Question

66

A **** ********** ** ********** a ********** ***** to ******* the ***** cost of producing a ***** of ******* ******* boards as * linear ******** of batch size **** ****** ** ****** ******** ** *** *** ** batch) ********** plant (Kingsland *** Yorktown) *** production shift (day *** ******** ** this ***** ***************** *** ******* * 2)
a ********

********* ** ***********

variable
a ************

variable
* *********

********* * *********

******** 77

* multiple ********** analysis ******** *** ********* tables:
********* ************

******** ***** * Statistic p-value
Intercept 6166849

******* ******* ******** x1 *******

******* ******* 0170675
** *******

0335605 ****** 583E-05
****** **

** MS F ******** Regression *

****** 6089148 1476117 ******** ******** **

******* ******** ***** 17

******** *** **********

******** *** **** ******** is: (Points * *** * *

******* * ****** ** * ******* *** * *

******* – ****** x1 * ****** *** * *

******* * ****** ** * ******* *** y =

1545535 + ******* x1 + 0335605 x2
y =

******* * ****** x1 * ******* *** Question **

A ******** ********** ******** produced the ********* ******** ********* ************

Standard ***** t Statistic ******** ********* 7520833

******* ******* 0042132
** *******

****** ******* ******** ** 1908183

******* ******* ******* ****** **

** ** * ******** ********** *

2036933 1018467 ******* ******** ******** **

******* ******** ***** **

******** ***** *******

******** ***** ******* * 2)
**** **

*** predictor variables *** *********** ** the ** ****** **** predictor

variable is *********** ** *** ** level
x1 is

the **** ********* ******** *********** ** *** ** ****** x2 **

*** only ********* variable significant ** the ** level
the *********

** *** *********** at *** ** ****** ******** **

* **** ****** appraiser ** ********** * ********** ***** to predict *** ****** value ** ****** ****** *********** ****** ** a function ** ****** **** ****** of ******** ****** of bathrooms *** ** *** house *** central ******* **** no) The ******** ******** ** this ***** *** ******* * *** ****** area

****** **

********* ****** value

central heating

*********** houses

******** ****

** ********** analysis ******** *** ** ********** ** ********* **** ******* : *** *********** of

determination
*********** **

************ ******** for

*** ******* ************* ********** *********

*****


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