Answer :
Final answer:
In the realm of tourism, the size and daily cost of rental properties can have a linear relationship determined by firstly creating a scatter plot for a visual representation, then calculating the correlation coefficient for quantifiable relation strength. This can then be applied in a linear regression model to predict the daily cost based on property size.
Explanation:
To find the linear regression equation between the size (x) of rental properties and their daily cost (y) in the field of tourism, you can use a combination of the given techniques. However, primarily the scatter plot and correlation coefficient techniques will be applied.
A scatter plot can be used first, as it gives a visual representation of the data. By plotting the property size against its daily cost, this technique can help identify any visible linear relationship between these two variables.
Once this relationship is established visually, the correlation coefficient can be calculated. This statistical measure ranges from -1 to 1, and it provides the strength and direction of a linear relationship between two variables. A value closer to -1 indicates a strong negative linear relationship, a value closer to 1 indicates a strong positive linear relationship, and a value near 0 suggests a weak or no linear relationship.
Moving on to a linear regression model, this will help us predict the dependent variable (y - daily cost) from the independent variable (x - property size). The model is represented as ŷ = a + bx, where 'a' is the y-intercept, 'b' is the slope of the line and 'x' is the property size. The correlation coefficient will help in assessing the appropriateness of this linear regression model.
To summarise, both the scatter plot and correlation coefficient are effective techniques for determining the linear regression equation between the size and cost/day of rental properties in the tourism industry.
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