Consider the following time series dataset representing the monthly sales of a product over a one-year period: | Month | Sales | |----------------| | 150 | | 180 | | 200 | 160 | | 210 | | Jan Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | 250 | | 300 | | 350 | 280 | | | 220 | | 190 | | 230 | • Plot the time series data to visualize the sales pattern over the year. Identify any trends or seasonality in the data. • Calculate the 3-month moving average for the sales data. Plot both the original sales data and the moving average on the same graph. Discuss how the moving average smoothens the data and highlights trends.
Consider the following time series dataset representing the monthly sales of a product over a one-year period: | Month | Sales | |----------------| | 150 | | 180 | | 200 | 160 | | 210 | | Jan Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | 250 | | 300 | | 350 | 280 | | | 220 | | 190 | | 230 | • Plot the time series data to visualize the sales pattern over the year. Identify any trends or seasonality in the data. • Calculate the 3-month moving average for the sales data. Plot both the original sales data and the moving average on the same graph. Discuss how the moving average smoothens the data and highlights trends.
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
Transcribed Image Text:Consider the following time series dataset representing the monthly sales
of a product over a one-year period:
| Month | Sales |
|----------------|
| 150 |
| 180 |
| 200 |
| 160 |
|210 |
| Jan
| Feb
| Mar
| Apr
| May
| Jun
| Jul
| Aug
| Sep
| Oct
| Nov
| Dec
| 250 |
| 300 |
| 350 |
280 |
| 220 |
| 190 |
| 230 |
• Plot the time series data to visualize the sales pattern over the year.
Identify any trends or seasonality in the data.
• Calculate the 3-month moving average for the sales data. Plot both the
original sales data and the moving average on the same graph.
Discuss how the moving average smoothens the data and highlights
trends.

Transcribed Image Text:Pop. Mean Stand. Dev. Sample size
1 73.00 10.00
6.00
14
2
62.50
8
1.Independent random samples are
selected from two populations. Below
are selected summary statistics.
(a) Construct the 95% confidence interval for μx-µY.
(b) Obtain the P-value for the alternative µx =µY.
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