# Statistics Assignment | Professional Writing Services

1. Ashely is senior at GWU and will be graduating in 3-4 weeks. When she started at GWU in the Fall of 2014, she decided to use an index for her basic spending for each semester. She compiled her data at the end each semester (after the final exams). Her data (fictitious) is provided below

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Item                Cost                Quantity

2014-Fall        Textbooks      \$100               6

Pizza               \$15                 30

Personal         \$50                 5

2015-Spring   Textbooks      \$120               5

Pizza               \$12                 25

Personal         \$50                 5

2015-Fall        Textbooks      \$110               7

Pizza               \$20                 20

Personal         \$50                 7

2016-Spring   Textbooks      \$100               4

Pizza               \$18                 25

Personal         \$100               8

2016-Fall        Textbooks      \$150               4

Pizza               \$15                 30

Personal         \$100               4

2017-Spring   Textbooks      \$150               5

Pizza               \$15                 10

Personal         \$80                 8

2017-Fall        Textbooks      \$150               8

Pizza               \$15                 20

Personal         \$80                 10

2018-Spring   Textbooks      \$N/A              N/A

Pizza               \$N/A              N/A

Personal         \$N/A              N/A

1.    Compute Simple price index for textbook for Fall of 2017. Use Fall of 2014 as the base. (1 pt)

2.    Compute Lasperyres and Paasche and Fisher indices for the Fall of 2017.  Use Fall of 2014 as the base period. 1 pt each

3.    Compute CPI (Lowe’s) indices for each semester using the fall of 2014 as the base period. (3pts)

4.    Use simple exponential smoothing with w=0.6 to forecast the CPI index for the spring of 2018. (1pt)

5.    Use exponential smoothing with trends (Holts’ method) with w=0.6 and n=0.3 to forecast the CPI index for the spring of 2018. (2 pts)

6.    Which one of the above forecast techniques you prefer? Why? (1)

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