Math Core Project The individual project for this class is linear regression : finding the best - fitting line for a set of ordered pairs (x, y) and then using the equation of that line to predict a new y - value for a given x - value. The first step in thi s process is determining if there is a strong linear correlation among the ordered pairs . I f the points come close to forming a straight line when plotted on a coordinate plane, there is a strong linear correlation . You will be using Microsoft Excel for this project. 1. Explanation of Data and Source For this project you will use population data. Look up the population of a city, county, state, or country for the past 5 years. For each data pair, let x represent the number of years after 2000 and le t y represent the population for that year. Explain the source of the data an d what it represents . (NOTE: A good source of population data is www.recenter.tamu.edu . Click “Data” and then “Population” to ob tain data.) 2. Data Table with x and y Properly Identified Present the pairs of numbers in table form. If you are doing a project with years, you must set up a correspondence such as x = the number of years after ____ (your starting ye ar). This mus t be done because you cannot break the x - axis on the graph. For this project you are using population data for the past 5 years. Therefore, you will use the correspondence x = the number of years after 2000. List the x - values and the years they re present in the x column. List the population for each year in the y column. 3. Correlation Coefficient The correlation coefficient (r) is a measure of the linear correlation of the data (i.e., how close the data points come to forming a straight lin e). The correlation coefficient is a number between - 1 and 1. If r is close to 0, it means there is little correlation (bad data set). If r is close to 1 , it means there is a strong positive correlation (the y - values are increasing). If r is close to - 1, it means there is a strong negative correlation (the y - values are decreasing) . The value of the correlation coefficient also indicates how accurately the regression equation can be expected to predict future outcomes. Calculating the Correlation C oefficient (r) in Excel 20 10 Click on the Page Layout tab. Click on Orientation. Click on Landscape. Enter the x – values in column A. Enter the y – values in column B. Click on cell D1, and click on Insert Function (fx). Select the category Statistical. ( Click on it.) Select a function: CORREL. (Click on it and then click OK.) Click in the box for Array1. Highlight the x−values; when you release the mouse button, they should be entered automatically . Click in the box for Array2. Highlight the y−values ; w hen you release the mouse button, they should be entered automatically . Click OK. The correlation coefficient of the data should appear in cell D1. In cell E1 , type an “r” to label this value as the correlation coefficient.

Subject | Mathematics |

Due By (Pacific Time) | 04/07/2013 12:00 am |

Tutor | Rating |
---|---|

pallavi Chat Now! |
out of 1971 reviews More.. |

amosmm Chat Now! |
out of 766 reviews More.. |

PhyzKyd Chat Now! |
out of 1164 reviews More.. |

rajdeep77 Chat Now! |
out of 721 reviews More.. |

sctys Chat Now! |
out of 1600 reviews More.. |

sharadgreen Chat Now! |
out of 770 reviews More.. |

topnotcher Chat Now! |
out of 766 reviews More.. |

XXXIAO Chat Now! |
out of 680 reviews More.. |