CONSUMER DEMAND MODEL
Title:
COEFFICIENTS AND PARAMETERS
Description
Constant
Formulas
Demand function
Inverse demand function
Formula for parameter A
Demand for Electricity
Symbol
c
Value
500
Sign
NA
d
10

Coefficient on Price of TV
e
0.3

Coefficien
Q1.
a)
QD= + PE +
where QD = quantity demanded of electricity (KWh per month)
PE = electricity price (cents per KWh)
NRE 570
Homework #2 Solutions
Winter
2015
b)
Yes. The coefficient estimate for is significantly different from 0 at the 0.1 level. The p
ANOVA Notes
ANOVA (Analysis of variance) Analysis of variance. A statistical test
with a continuous dependent variable and categorical independent
variable(s). It generalizes ttest to more than two groups, without increasing
the chance of committing a ty
Final Review Session
April 27, 2015
Final Exam Logistics
Thursday April 30
1040 Dana
10:3012:30
25% of Final Grade
Bring a calculator!
Formula Cards
2 index cards, front and back
Can include formulas with the name of the
test it is used for
Can not in
Review
Probability distributions
Ztests
 Single value
 Mean
Central Limit theorem
Zstatistic for a mean
Due to CLT, we can use Z for a sample
mean taken from a population
Use when:
sample taken from the population
mu and sigma are known
of
Que
Review
Sampling
Simple random
Stratied random
Systematic
Probability rules
Unions and intersections
Permutations and combinations
Sets  combinations
Similar to permutations but order does not matter
All possible groupings without resampling
n!
n
NRE 538
Natural Resource Statistics
Dr. Shikha Marwah
Justin Burdine (GSI)
Karl Bosse (GSI)
Basic info
My background
Contact info  Email is best
([email protected])
Meeting times
Lecture: Mon & Wed 2:304:00
Labs:
Thurs 3:005:00 (Justin)
Thurs 5:007
ANOVA
For all the following problems, report where applicable (1) which ANOVA to use, (2)
null hypothesis, (3) parametric model, (4) ANOVA table, (5) conclusion regarding the
null hypothesis. For all problems = 0.05 unless otherwise stated.
1. You are int
SIMPLE LINEAR REGRESSION
For all problems, report where applicable (1) null hypothesis, (2) parametric model,
(3) ANOVA table or ttest results, (5) conclusions about the null hypothesis, and (6)
pvalues. For all p
ANOVA SOLUTIONS
1. Randomized block oneway ANOVA
* block null and some calculations that are optional are in brackets.
The answer would still be completely correct if you excluded all parts
in brackets.
H0: Method has no effect on DO measurements
[H
SIMPLE LINEAR REGRESSION SOLUTIONS
1. You are planning on planting cucumbers in your garden this summer and
want to know how many you will have by the end of the year. You conduct a
regression analysis and find
Review
What is statistics?
Difference between a measurement,
observation, sample, and population
Statistical inference
Central tendency
Measuresofasample/population
12
Locationorcentraltendency
Dispersion,scatter,orspread
Variance,standarddeviation
Final Exam Review
NRE 538
April 16, 2015
Exam I Review
Definitions
Type I & Type II Error
Population vs. Sample
Variables (independent vs. dependent & discrete vs. continuous)
Z test (single value and one
sample)
Twosample ttest
Paired Ttest
Con
Review
Oneway ANOVA
Multiple comparison tests (MCT)
Tukeys HSD test
Randomized block ANOVA
Twoway ANOVA
Multiway ANOVAs
More complex ANOVAs (more than 2 factors) are
possible and encountered relatively often
For each additional factor, you add another
INDEPENDENT PROJECT
Natural Resource Statistics  Winter 2015
Instructions: Each student is expected to complete a project where they will independently do the
following:
1. develop a research question
2. design an experiment (or data collection) to answe
Remaining Schedule
This week: Miscellaneous Advanced Statistics and
Multivariate Data Analysis
Mon 4/20: Lecture wrapup and Review
Reminders:
Thursday 4/30: Final Exam (10:3012:30 in Dana 1040)
Friday 5 p.m. 4/17: Final project due
4/11  4/24: Teach
Remaining Schedule
This week: Miscellaneous Advanced Statistics and
Multivariate Data Analysis
Mon 4/20: Lecture wrapup and Review
Reminders:
Thursday 4/30: Final Exam (10:3012:30 in Dana 1040)
Friday 5 p.m. 4/17: Final project due
4/11  4/24: Teach
Independent Project
Abstract  overview of the study
Introduction  general info and hypotheses
Methods  statistical analysis and justication of
choice of test
Results  text, tables and at least one gure
Discussion
Independent Project
Appendix  include
Lecture wrapup/Review
Review sessions
Monday, April 27 from 12  2 p.m. Dana 1028 (Justin)
Monday, April 27 from 911 a.m. Dana 1028 (Karl)
April 24: Final day for teaching evaluations
(Justin, Karl and I would greatly appreciate your feedback)
Thursday,
Assumptions of ANOVA
Linear  linear relationship between y and covariate
Independent  y values are sampled randomly and
independent of each other
Normality  the residuals are normally distributed
Equal variance  variance is equal across all x values
a
Linear regression
Regression is used to analyze relationships between 2+
continuous variables
Simple linear regression is the specic case where there
are just two continuous variables
As with ANOVA we can use sum of squares to determine
the relationship b
Review
Simple Linear Regression
ANOVA method
ttest method
Condence interval/bands
Prediction interval/bands
Next Monday (3/23): Exam 2
Wednesday: 10noon
Extra ofce hours:
Thursday:10noon
Friday: 10noon
Assumptions of linear regression
Linear  a lin
Part lll
Correlation
Multiple Regression
Statistical Modeling
ANCOVA
Graphing data
Nonparametric tests
Multivariate data analysis
Model Selection
Process of choosing the appropriate model (from
predictor variables) to describe your data
A model is a math