Instructions: Use the technology of your choice (calculator, Excel, GeoGebra, Google Sheets) to find the regression line, the correlation coefficient of the following data sets, and interpolate or extrapolate the requested data. (Round all numbers to the nearest hundredth, when necessary.) Data Set: {(0,7), (1,5), (1.5, 3), (2, 5), (2.3, 3.2), (3, 2), (3.5, 4)} 1. The regression line is: y = 6.09 1.01 2. Based on the regression line, we would expect the value of response variable to be when the explanatory variable is 0. (NOTE: This is the y-intercept.) 3. For each increase of 1 in of the explanatory variable, we can expect a(n) decrease of in the response variable. (NOTE: This is the slope.) 4. If x = 2.5, the y = This is an example of interpolation %3D 5. The correlation coefficient is r = -0.73
Quadratic Equation
When it comes to the concept of polynomial equations, quadratic equations can be said to be a special case. What does solving a quadratic equation mean? We will understand the quadratics and their types once we are familiar with the polynomial equations and their types.
Demand and Supply Function
The concept of demand and supply is important for various factors. One of them is studying and evaluating the condition of an economy within a given period of time. The analysis or evaluation of the demand side factors are important for the suppliers to understand the consumer behavior. The evaluation of supply side factors is important for the consumers in order to understand that what kind of combination of goods or what kind of goods and services he or she should consume in order to maximize his utility and minimize the cost. Therefore, in microeconomics both of these concepts are extremely important in order to have an idea that what exactly is going on in the economy.
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