FUSARIUM INFESTATION IN TOMATO
INTRODUCTION
The disease symptoms and lab analysis on the crop show clear indications of fungal infection in
your green house, its spreads very fast and if no immediate measures are taken all the crops in
the greenhouse will
Review of Probability and
Statistics
(i.e. things you learned in Maths and
Maths for Economists and need to
remember to do well in this class!)
1
Random Variables
X is a random variable if it represents a random
draw from some population
a discrete random
Multiple Regression Analysis
y = 0 + 1x1 + 2x2 + . . . kxk + u
2. Inference
1
Assumptions of the Classical
Linear Model (CLM)
So far, we know that given the GaussMarkov assumptions, OLS is BLUE,
In order to do classical hypothesis testing,
we need to add
CAT I Tue 3/04/2015
CAT II Tue 16/04/2015
EGERTON UNIVERSITY
FACULTY OF ENGINEERING AND TECHNOLOGY
DEPARTMENT OF AGRICULTURAL ENGINEERING
AGEN 462: RESEARCH METHODS
COURSE OUTLINE
INSTRUCTOR: Mr. Moses Muiruri
5/26/16
Mr. Moses muiruri
1
COURSE DESCRIPTIO
PROPERTIES OF THE MULTIPLE REGRESSION COEFFICIENTS
A.1: The model is linear in parameters and correctly specified.
Y 1 2 X 2 . k X k u
A.2: There does not exist an exact linear relationship among the
regressors in the sample.
A.3 The disturbance term has
HETEROSCEDASTICITY-CONSISTENT STANDARD ERRORS
OLS
2
b
n
2 a i ui
i 1
where
ai
(Xi X )
n
2
(
X
X
)
i
i 1
Heteroscedasticity causes OLS standard errors to be biased is finite samples. However it
can be demonstrated that they are nevertheless consistent,
HETEROSCEDASTICITY-CONSISTENT STANDARD ERRORS
OLS
2
b
n
2 a i ui
i 1
where
ai
(Xi X )
n
2
(
X
X
)
i
i 1
Heteroscedasticity causes OLS standard errors to be biased is finite samples. However it
can be demonstrated that they are nevertheless consistent,
PROPERTIES OF THE MULTIPLE REGRESSION COEFFICIENTS
A.1: The model is linear in parameters and correctly specified.
Y 1 2 X 2 . k X k u
A.2: There does not exist an exact linear relationship among the
regressors in the sample.
A.3 The disturbance term has
Introduction to Econometrics
Lecture 1
Introduction and overview of the course
Definition, scope and methodology of
econometrics
A review of the simple (bivariate) linear
regression model
INEMET [U13783]
1
Objectives
To provide you with information about
Representing technology in a one
output and two Input case
So far problems faced by a farmer
wishing to determine how much of a single
input to use or how much of a single
output to produce to maximize profits were
addressed.
Suppose instead that two in
group V
Topic: Risk and Uncertainty
Grace ,Joseph and Bernard
1
Agenda
Defining Risk and Its Different Types
Explain expected utility
Understand risk aversion
Management Tools for Risk
Deciding whether to insure
2
Very few business decisions involve certa
THE COBB-DOUGLAS PRODUCTION FUNCTION
1.1 Introduction
The paper describing the Cobb Douglas production function was published in the
journal American Economic Review in 1928. The original article dealt with an early
empirical effort to estimate the compar
Unconstrained profit Maximization with Two Inputs
The criteria for maximizing a function can be
further illustrated with an agricultural example
using a profit function for corn.
y = f(x1, x2)
where y = corn yield in bushels per acre
x1 = pounds of po
Grace ,Joseph and Bernard
1
Agenda
Defining Risk and Its Different Types
Explain expected utility
Understand risk aversion
Management Tools for Risk
Deciding whether to insure
2
Very few business decisions involve certainty in
which an action invariably l
Grace ,Joseph and Bernard
1
Agenda
Defining Risk and Its Different Types
Explain expected utility
Understanding risk aversion
Management Tools for Risk
Insurance decisions
2
Definition of Uncertainty
In an uncertain
environment, possible
outcomes and thei
The CES Production Functions
The constant elasticity of substitution production functions dominates in applied
research. The parametric structure is
(1)
1/
Y = A [ (aKK) + (1-) (aNN) ]
.
Here 0 < < 1 is the share parameter and determines the degree of su
THE COBB-DOUGLAS PRODUCTION FUNCTION
1.1 Introduction
The paper describing the Cobb Douglas production function was published in the
journal American Economic Review in 1928. The original article dealt with an early
empirical effort to estimate the compar
Graphical Method
Introduction
An optimal as well as feasible solution to an
LP problem is obtained by choosing from
several values of decision variables X1,
X2.Xn, the one set of constraints
simultaneously and also provides the
optimal ( maximum or minim
Homogeneous Production Functions
The terms Economy or diseconomy of scale are
defined with reference to a particular class of
production functions, known as homogeneous
production functions.
A production function is said to be homogeneous of
degree n if
Homogeneous Production Functions
The terms Economy or diseconomy of scale are
defined with reference to a particular class of
production functions, known as homogeneous
production functions.
A production function is said to be homogeneous of
degree n if
The Simplex Method
Maximize
p= 4y1 + 5y2
where y1 and y2 are two commodities.
The 4 and 5 represent the price per unit of y1 and
y2,
respectively.
The constraints are
2y1 + 1y2 <_ 12
1y1 + 2y2 <_ 16
y1, y2 >_ 0
Simplex contd
The first step is to intr
PRESENTED BY:
NAME:
REG.NO.
OLOO IDI GEORGE
KM15/2469/09
HEZRON NYARINDO ISABOKE
KM17/2399/09
REBECCAH WAIRIMU WANJIRU
KM17/2405/09
Linear Programming
Learning Objectives
To understand the LP assumptions
Appreciate the Application of LP
Apply the methods
22.1 Introduction
22.2 Classical Optimization and Linear Programming
Linear programming involves the maximization or minimization of a linear function
subject to linear constraints. Unlike classical optimization problems, in which at least one of the
func
1
The CES production function
The homogenous Constant Elasticity of Substitution (CES) production function takes the form
n
o 1/
Q = K +(1 )L
exp(U ), 1, 0 1, > 0, (1)
where K is capital, L is labor, Q is output, and U is an error term satisfying
E[U |K,
OBJECTIVES
To distinguish between the concept of size and scale
To demonstrate graphically a case where we have
economies of scale, constant returns to scale and
diseconomies of scale
ECONOMIES OF SIZE
It can be looked at in 3 dimensions
1)Seeks to answer
Chapter 6
5/1/16 05:28:37 AM
Uncertainty, Default, and Risk
We maintain the assumptions of the previous chapter:
We assume perfect markets, so we assume four market features:
1. No differences in opinion.
2. No taxes.
3. No transaction costs.
4. No big s
Homogeneous Production Functions
The terms Economy or diseconomy of scale are
defined with reference to a particular class of
production functions, known as homogeneous
production functions.
A production function is said to be homogeneous of
degree n if
Risk and Uncertainty
Vani K Borooah
University of Ulster
Basic Concepts
Gamble: An action with more than one possible
outcome, such that with each outcome there is an
associated probability of that outcome occurring. If
the outcomes are good (G) and bad (
Maximizing a Profit Function with Two Inputs
The criteria for maximizing a function can be further illustrated with
an agricultural example using a profit function for corn. Suppose that the
production function
for corn is given by
y = f(x1, x2)
where y =
COBB-DOUGLAS
PRODUCTION
FUNCTION
INTRODUCTION
Cobb-Douglas is the most
famous of all production
functions used to represent
production processes both
in and out of agriculture.
It was published in 1928 in an empirical
study dealing with the productivity