Exams are coming!
Get ready with premium notes and study guides!

Textbook Notes for Olga Kraminer

YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter 16: CH 16 Notes part1

OC2959075 Page
20 Feb 2017
0
The purpose of simple regression analysis is to predict the value of one variable based on the value of one other variable using a mathematical equatio
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter Notes - Chapter 13: Variance, F-Distribution, Test Statistic

OC2959076 Page
20 Feb 2017
0
Chapter 13 remember when you test if two variances are equal the. Significance level are always 0. 05 and the df formula is always rounded. For f-distr
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter 12: CH 12 Notes

OC2959073 Page
20 Feb 2017
0
While the (cid:374)or(cid:373)al distri(cid:271)utio(cid:374)"s shape a(cid:374)d lo(cid:272)atio(cid:374) are influenced by the mean and standard devi
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter Notes - Chapter 16: Explained Variation, Total Variation, Bias Of An Estimator

OC2959075 Page
20 Feb 2017
0
So when sse is small, the fit is excellent and the model should be used. We judge the value of see by comparing to the mean of the dependant variable (
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter Notes - Chapter 10: Bias Of An Estimator, Confidence Interval, Point Estimation

OC2959074 Page
20 Feb 2017
0
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter 11: CH 11 Notes

OC2959073 Page
20 Feb 2017
0
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter Notes - Chapter 9: Central Limit Theorem, Sampling Distribution, Standard Deviation

OC2959073 Page
20 Feb 2017
1
2 methods to create a sampling distribution. 2nd method relies on the rules of probability, lar of expected values and variance. Because the value of t
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter Notes - Chapter 14: Variance, Null Hypothesis, Dependent And Independent Variables

OC2959075 Page
20 Feb 2017
0
View Document
YORKMGMT 1050Olga KraminerFall

MGMT 1050 Chapter Notes - Chapter 7: Continuous Or Discrete Variable, Random Variable, Standard Deviation

OC2959073 Page
20 Feb 2017
1
Random variable is a function or rule that assigns a number to each outcome of a experiment. Simply stated the value of a random variable is a numerica
View Document
Showing 1 — 9 of 9 results

Textbook Notes (280,000)
CA (170,000)
York (10,000)
MGMT (200)
Olga Kraminer (9)