The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4​ months: Month Jan Feb Mar Apr Number of Accidents 25 48 60 90 Using the least-squares regressionLOADING... ​method, the trend equation for forecasting is ​(round your responses to two decimal ​places)​: ModifyingAbove y with caret ​= nothing ​+ nothingx Using​ least-squares regression, the forecast for the number of accidents that will occur in the month of May​ = nothing accidents​ (enter your response as a whole​ number).

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Answer:

The forecast of number of accidents that will occur in the month of May shows that there will be 108 accidents by May

Step-by-step explanation:

The lease square method is also known as regression method on excel.

y = mx + c

where a is the intersect and b is the slope

Step 1: get the slope 'm' by using the command =SLOPE(C2:C5,A2:A5)

Step 2: get the intersect 'c' by using the command =INTERSECT(C2:C5,A2:A5)

c=4 , m=20.7 and x is the period

Step 3: Calculate 'forcast' for each month using the commands =B$9+B$8*A2 on D2 and copy down to May.

Y = mx + c

You should get 107.5 ≈ 108 accidents

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A number of accidents in Florida.

The following data provide us the number of accidents that occurred in Florida state on the highway of 101 during the last four months. The months are given from Jan to April in number of accidents as 25, 48, 60, and 90. The loading methods and the least square method have been used for forecasting.

Thus the answer is 108 accidents in may month.

  • As per the given data, the lease sq method is called as the regression method given by the formula of y = MX + c. Here, a is the intersect and b is the slope
  • The first step is to get the slope of 'm' by using the commands =SLOPE (C2:C5,A2:A5) The next step is to get the intersect 'c' by =INTERSECT of (C2:C5,A2:A5)Thus output as c=4 , m=20.7 and x is the period. In last step the forecast for each month using the command =B$9+B$8*A2 on D2
  • Hence the number of accidents that occurred in may where 107.5 = 108 accidents.

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