Econometrics 1: A Review of Statistical Concepts 1.1 - Random Variables, Distribution and Density Functions Flashcards

1
Q

What type of variables are usually dealt with in Econometrics?

A

Random continuous variables

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2
Q

What are the names of the graphs that depict the probabilities associated with the values taken by random variables

A

Density & distribution functions

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3
Q

What do density & distribution functions do?

A

They depict the probabilities associated with the values taken by random variables

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4
Q

Describe the density function of a random variable

A

The density function of a random variable 𝑋 is often
denoted 𝑓(π‘₯). The x-axis, β€˜X’, represents the continuous range of values over which the random variable 𝑋 exists and
the y-axis, β€˜f(x)’, is the value of the density function. The probabilities associated with variable 𝑋 are
measured by areas under the density function (under the curve). So, for example, the probability
that the value of 𝑋 will be between the values π‘Ž and 𝑏 is equal to the value of… let’s say area 𝐴, i.e. Area 𝐴
𝑃(π‘Ž < 𝑋 < 𝑏) = ∫with upper limit of a and lower limit of b 𝑓(π‘₯)𝑑π‘₯. Hence calculating probabilities from density functions requires
integration. A feature of random variables and their densities is that the area under the whole density is equal
to unity, i.e. ∫ with upper limit of ∞ and lower limit of -∞ 𝑓(π‘₯)𝑑π‘₯ = 1. Why is this? Let’s suppose that the variable can only take on values in the range 0 to 10. Then the probability of the variable taking on a value between 0 and 10 has to
be 1 and therefore ∫ with upper limit of 10 and lower limit of 0 𝑓(π‘₯)𝑑π‘₯ = 1

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5
Q

Describe the distribution function of a random variable

A

Related to the density function is the distribution function, often denoted 𝐹(π‘₯), which depicts the
probability that 𝑋 takes on values less than π‘₯, i.e. 𝐹(π‘Ž) = 𝑃(𝑋 ≀ π‘Ž) = ∫*upper bound β€˜π‘Žβ€™ and lower bound β€˜βˆ’βˆžβ€™ *𝑓(π‘₯)𝑑π‘₯ where π‘Ž is a number. The distribution therefore shows the accumulation of the probabilities associated with values of 𝑋 up to 𝑋 = π‘Ž. For the density function drawn above, this will look something like the
following:
Graph with y-axis β€˜F(x)’ and x-axis β€˜X’ with cubic line. It’s asymptotic to a horizontal dotted line at the top of the graph labelled β€˜1’ at y-axis. There’s also a horizontal dotted line lower down in the graph, labelled β€˜F(π‘Ž)’ at y-axis, that meets the line; at that point, there’s a dotted vertical line, labelled β€˜π‘Žβ€™ at x-axis.
The distribution function point 𝐹(π‘Ž) represents the area under the density function up to the value
π‘Ž.

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