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1. A) Explanatory Variable = X (Years spent in school after High School)
Dependent Variable = Y (Income in 10 thousands of dollars)
Income in 10000s vs Years Spent in School after High School
8
7
6
5
Income in 10000s of Dollars
4
3
2
1
0
0
1
2
3
4
5
6
7
8
1. A) Explanatory Variable = X (Years spent in school after High School)
Dependent Variable = Y (Income in 10 thousands of dollars)
Income in 10000s of Dollars
Income in 10000s vs Years Spent in
School after High School
8
7
6
5
4
3
Series1
2
1
0
0
2
4
6
8
You have just been selected to manage Product Line 1. Available to you
are the following sets of data:
1. Cost C and output x during the past seven production/sales periods.
2. Demand x and unit price p data during the past six production/sales
periods.
D
NCSS Statistical Software
NCSS.com
Chapter 545
ROC Curves
Introduction
This procedure generates both binormal and empirical (nonparametric) ROC curves. It computes comparative
measures such as the whole, and partial, area under the ROC curve. It provides
NCSS Statistical Software
NCSS.com
Chapter 345
Nondetects Data
Regression
Introduction
This module fits the regression relationship between a positive-valued dependent variable (with, possibly, some
nondetected responses) and one or more independent varia
NCSS Statistical Software
NCSS.com
Chapter 575
Probit Analysis
Introduction
Probit Analysis is a method of analyzing the relationship between a stimulus (dose) and the quantal (all or
nothing) response. Quantitative responses are almost always preferred,
NCSS Statistical Software
NCSS.com
Chapter 530
Loglinear Models
Introduction
Loglinear models (LLM) studies the relationships among two or more discrete variables. Often referred to as
multiway frequency analysis, it is an extension of the familiar chi-sq
NCSS Statistical Software
NCSS.com
Chapter 400
Canonical Correlation
Introduction
Canonical correlation analysis is the study of the linear relations between two sets of variables. It is the
multivariate extension of correlation analysis. Although we will