forecasting_lecture_03

# forecasting_lecture_03 - Lecture Notes 3 1 Types of...

This preview shows pages 1–4. Sign up to view the full content.

1 Lecture Notes 3 1. Types of economic variables (i) Continuous variable – takes on a continuum in the sample space, such as all points on a line or all real numbers Example: GDP, Pollution concentration, etc. (ii) Discrete variables – finite number of elements or an infinitely countable number, such as all positive integers. Example: Number of workers, etc. (iii) Categorical data are grouped accordingly to some quality or attribute Example: Sex or type of automobile. 2. Review of statistics (i) Population – the total group set of elements of interest. Sample – a subset of the population. We usually collect samples because it is too costly to sample the entire population. Example – College students’ survey in Kazakhstan Population is all college students Probability – the relative frequency or occurrence of an event after repetitive trials or experiments. Probability lies between 0 and 1 All probabilities for all events have to sum to 1 Example: 60% chance of rain today Implies a 40% of no rain, summing to one or 100%

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
2 (ii) Probability distribution functions (PDF) – a function that associates each value of a discrete random variable with the probability that this value will occur. Denoted as p(x) or f(x) Cumulative probability distribution function (CDF) - integral of a probability function Denoted by a capital letter, such as P(x) or F(x).     x dt t f x P If you sum over all probabilities, then it has to equal one.     1  dt t f x P The normal probability distribution is shown below
(iii) Descriptive statistical measures – describe a sample or population. Measures of central tendencies Mean – calculated by ) x ( f x x i i where f(x) is the pdf and x is the random variable. This is also the expected value If every observation is equally likely, then i x n 1 x where n is the number of observations Median – the middle point or observation when the data are ordered from smallest to largest. Mode – the value, which occurs most often in a distribution. The peak of a distribution Use calculus to find maximum value Range – the difference between the largest value in the sample (the maximum) and the smallest value (the minimum), min max x x R Variance – is a measure of deviation from the mean, denoted by 2 Variance has a problem If the units are in \$’s, then variance is \$ 2 The n-1 is the sample variance Degrees of freedom (df) – the amount of information you have, i.e. the number of observations Since you estimated the variance, you lose one piece of

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 13

forecasting_lecture_03 - Lecture Notes 3 1 Types of...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online