Quantitative data analysis. Module in research methods course for tourism program Reza Mortazavi 2014 Lecture 4. Relationship between variables. Correlation When two variables are linearly related (or covary ) we say they are correlated either positively or negatively.
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Quantitative data analysis
Module in research methods course for tourism program
Interpret the output!
For example, food consumption or tourism demand depends on income.
2. Forecast or predict the value of one variable, y, based on the value of another variable, x.
y = dollars spent each week on food items.
x = consumer’s weekly income.
The relationship between x and the expected value of y , given x, might belinear:E(y|x) = b1 + b2 x
Probability Distribution of Food Expenditures given
income x=$480 and x=$800.
a linear relationship between average expenditure
on food and income.
The population parametersb1andb2are unknown population constants.
The formulas that produce thesample estimates b1 and b2 arecalled the estimators of b1andb2.
When b1 and b2 are used to representthe formulas rather than specific values,they are called estimators of b1andb2which are random variables becausethey are different from sample to sample.
Well: 411.123+ 1.03526*200= 618. 18
This is a point (prediction) estimate. We can calculate say a 95% confidence (prediction) interval.
95 % PI: (570.1205-666.2293)