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Summary Maths Stats 246 Part 1 $5.68   Add to cart

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Summary Maths Stats 246 Part 1

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These notes summarise the first part of the maths stats 246 syllabus at stellenbosch university. the notes include theory as well as numerous worked examples with explanation.

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  • July 18, 2022
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  • 2021/2022
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Maths stats246


Introduction


Models
playa vitally important roleinthesolutions to problems inpractice
In particular linear models are often used in decision processes
Linearstatisticmodels have a stochasticcomponent and are
typically multidimensional
These models are described
using vectors and matrices


classification of models s Physicalmodels

Abstract models

Quantitativeand qualitative mathematicalModels




Thestatisticalmodel


Thestatisticalmodel will be of theform

Y ft E
Where Y is the dependent variable f is a function of one or more quantifiablevariables

and E is the error in the model
Yis the variable of primaryinterest and can be seento be explained bythe
Variables in f so that Ely f
However it is generally the case that for numerical values of Y and variables in f
that fi the difference
can be attributed to measurement error
yi
specification

ie fi te
yi

,Exampleof LinearstatisticalModel s

A researcherexamines the impact of the number of hoursworked intelligence of
student abilityof lecturer and standard of test on how well a student performs

Test performance and hours worked can be measured but the other variables
cannot

The researcherdecides to use a statisticalmodeland include the qualitative
variables as partof the specification error inthe stochasticemerterm
X hoursstudied

Model I Yx f x Ex errorterm

testmark
Yxand Ex are stochastic variables

Nowtheresearcher mustdecide ontheform of f and wether X will be a stochastic

variable or not
Researcherassumes

feat at Bx and Ex Normal o 02



Researchertakestosamples

, cannow predict mark



NotationandBasicDefinitions



Asinglecolumn matrixwith n news is called a vector with n components

Let ai an beelementsfrom a field t then an n component vector

d
realentries
a
9s which is indicated also
by a nx
under

naigffr
an line column vector nrows x icolumn


The transpose of a nxt is a new vector consisting of n components and
m
transpose




If ei n Xi is a vector withthe ith componentequal to one and all other
components o thenthe identity matrix is
g g g
Nxnidentitymatrix

, An n component vector with all zeros is called the zerovector and canbe
written as o



Considertwo n component vectors X and Y The scalar
transposemustalwaysbeonleftside

X'y Y x É XiYi is called theinner product scalarproduct of
twovectors


Thetwo vectors X and Y are orthogonal if X'y Y x 0 The vector x

is normal if and only if
xx It Xi

Thelengthof x is defined as 1 11 X X É Xi
makelength 1
It followsthat the vector Y can be normalised
by dividing Y
by its
length
y
1141 thishaslengthofone unit
yy


Schwarzinequality

the absolute valueof the innerproduct of x and y
x y 11 11 my is smaller or equal to the product ofthe lengths of
X andY

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