Formatting a time series forecast



Regression analysis has done for the period Sept 1890 to Dec 1910 
between ratio of job placements to job seekers for Cincinnati- women between this and what?. R- Square Sometimes in the body of a report, you are forced to use jargon (in this case, statistical jargon). But, the report should start with standard English. Begin by saying what are the key findings of the investigation. Later, you may have to use the jargon of statistics to explain how you got those finding. is 59% as shown in the table below.

R 0.76989
R-square 0.59273
Adjusted R-square 0.58935
S 0.11531
N 244


  D.F. SS MS F P-level
Regression 2. 4.66389 2.33195 175.37561 0.
Residual 241. 3.20455 0.0133
Total 243. 7.86844


  Coefficient Standard Error LCL UCL T Stat P-level H0 (5%)


0.53664 0.01576 0.50559 0.56769 34.047 0. Rejected
Time 0.01417 0.00139 0.01143 0.0169 10.20118 0. Rejected
Bus Cycle


0.94448 0.09546 0.75643 1.13252 9.89389 0. Rejected

The regression is incorrect. I cannot figure out why. I will grade your interpretation of the output as you have it.

  • Whether the ratio is affected by the business cycle?

T state is greater than 1,96 it is significant.

Y = b0 + b1X1 + b2X2

Y = 0.536+ 0.014X1 + 0.944X2

Y is the job placement to seeker ratio, which is affected by business cycle index (X2).

  • Whether the ratio is particularly sensitive to the business cycle?

Y = 0.536+ 0.014X1 + 0.944X2

The estimate of the coefficient -1 standard errors is greater than 1 ?

The job placement to seeker ratio increases by .014 with one increase in time, holding all other things constant. I don’t know why this statement is here. The job placement to seeker ratio increases by 0.944 with every increase in business cycle, holding time constant.

This is not a clear statement.

  • Whether the ratio fell by at least as much as would be predicted following the panic of 1907?

The graph present a regression analysis between the ratio of job placements to job seekers for Cincinnati- females as dependent variables, Time and Business cycles as the independent variables. There is a positive correlation can found as they both are rising and going down quite simultaneously.

The chart shows the trends in business cycle from time period 1890 to 1910. There was a recession from 1893 to 1899, the economy recovered a little bit but it went through a recession after 1907. The job placement to seeker ratio decreases in the same time when there was recession and increases afterwards. Consequently business cycle had effect on job placement to seeker ratio for Cincinnati women.

The ratio of job placement to seeker did fall as it was predicted following the panic of 1907.

The red lines (time) shouldn’t be on the chart. It is implicit in the horizontal axis. Otherwise, this is an impressive chart.


Clifford F. Thies, Chapter 4 Time Series Analysis