ENVM 502
TECHNICAL REVIEW COURSE
ASSIGNMENT 8

Each item is worth 10 Points.

An electronics store provides the following data regarding the number of advertisements and the number of TV’s sold during an eight week period. Determine the correlation coefficient between the number of advertisements and the number of TV’s sold. Also, provide a graphical representation of the data below.

WEEK    1    2    3    4    5    6    7    8
# of Advertisements    12    30    10    20    45    36    25    21
# of TV’s Sold    25    38    18    25    57    30    32    23

1.    Develop a separate scatter diagram for each set of data (Week # vs. # of Advertisements and Week# vs. # of TV’s sold).

2.    Show the line of best fit for each set of data (Week # vs. # of Advertisements and Week# vs. # of TV’s sold).

3.    Define the equation for the line of best fit for each set of data (Week # vs. # of Advertisements and Week# vs. # of TV’s sold) and the correlation coefficient, r, for each.

4.    Prepare a figure which shows the scatter diagram and line of best fit that shows the relationship between the # of Advertisements and the # of TV’s sold.

5.    Define the equation for the line of best fit and its correlation coefficient for the Figure prepared in item “d” above.

6.    Given the equation and correlation coefficient which you have determined in item “e” above, describe the conclusion which you draw concerning the relationship between the number of Advertisements and the number of TV’s sold.

You may use Excel and/or Power Point or other tools to address the items above.

ENVM 502
TECHNICAL REVIEW COURSE
ASSIGNMENT 8

Each item is worth 10 Points.

An electronics store provides the following data regarding the number of advertisements and the number of TV’s sold during an eight week period. Determine the correlation coefficient between the number of advertisements and the number of TV’s sold. Also, provide a graphical representation of the data below.

WEEK    1    2    3    4    5    6    7    8
# of Advertisements    12    30    10    20    45    36    25    21
# of TV’s Sold    25    38    18    25    57    30    32    23

1.    Develop a separate scatter diagram for each set of data (Week # vs. # of Advertisements and Week# vs. # of TV’s sold).

2.    Show the line of best fit for each set of data (Week # vs. # of Advertisements and Week# vs. # of TV’s sold).

3.    Define the equation for the line of best fit for each set of data (Week # vs. # of Advertisements and Week# vs. # of TV’s sold) and the correlation coefficient, r, for each.

4.    Prepare a figure which shows the scatter diagram and line of best fit that shows the relationship between the # of Advertisements and the # of TV’s sold.

5.    Define the equation for the line of best fit and its correlation coefficient for the Figure prepared in item “d” above.

6.    Given the equation and correlation coefficient which you have determined in item “e” above, describe the conclusion which you draw concerning the relationship between the number of Advertisements and the number of TV’s sold.

You may use Excel and/or Power Point or other tools to address the items above.