Question: Linear Modeling Find a unique set of linear data, create a scatterplot of the data, apply curve-fitting techniques to find a linear model of the

Linear Modeling Find a unique set of linear data, create a scatterplot of the data, apply curve-fitting techniques to find a linear model of the data, assess the fit of this linear model to the data and interpret the results. (1) Find a unique set of Linear Data .... describe the topic, provide a table or list of data (at least 8 data points), and cite any sources for the data. The data must be unique. (2) Create a Scatterplot of the data .... This can be done using EXCEL, another graphing program (i.e., http://www.mathcracker.com/scatter_plot.php). A typical X-Y graph of (x,y) data points. Choose the X and Y axis and label the axes. The data should have some linear trend. The data should appear to have an upward or downward trend that could be estimated with a line. (3) Apply curve-fitting techniques to find a Linear Model ... Find the equation of a line that best fits the data. This is called a "Regression Line" and in the form of a typical linear equation: Y = mX+b, where m=slope and b=y-intercept. State the linear model equation and discuss the meaning of its slope in a sentence or two. Use EXCEL for this step, or one of many online "linear regression" or "simple regression" tools. Example ... http://people.hofstra.edu/Stefan_Waner/newgraph/regressionframes.html (4) Find the Correlation Coefficient ... Assess the fit of the linear model to the data by finding the "Correlation Coefficient", or "r". In most of the linear regression tools (EXCEL or online) you will find that they give you the r2 or r correlation results. Discuss the findings in a few sentences. Is the Correlation Coefficient (r) positive or negative? Is the linear relationship very strong, moderately strong, weak, or nonexistent? A set of data with a positive slope will have a positive correlation coefficient and a set of data with a negative slope will have a negative correlation coefficient. Check Examples of "strong" linear relationships and "poor" or "weak" linear relationships on the internet. A few examples are shown below. The closer "r" is to 1.0 or -1.0, the better the linear relationship. Submit work in WORD format. Project report should be about 1-2 pages and include the sections (1 to 4) listed above

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