Answer:
sec²(x) - sec(x) + tan²(x) = (sec(x) - 1)(2sec(x) + 1)
Step-by-step explanation:
sec²(x) - sec(x) + tan²(x) =
= sec²(x) - sec(x) + [sec²(x) - 1]
= sec²(x) - sec(x) + [(sec(x) + 1)(sec(x) - 1)]
= sec(x)[sec(x) - 1] + [(sec(x) + 1)(sec(x) - 1)]
= (sec(x) - 1)(sec(x) + sec(x) + 1)
= (sec(x) - 1)(2sec(x) + 1)
There is a 1/4 chance of getting the Blue Marble out of the bag. But when it is 2 in a row you have to multiply your chances so it would be 1/4 * 1/4 or 1/16
Answer:
a) 
b)
c)
Step-by-step explanation:
Assuming the following question: Because of staffing decisions, managers of the Gibson-Marimont Hotel are interested in the variability in the number of rooms occupied per day during a particular season of the year. A sample of 20 days of operation shows a sample mean of 290 rooms occupied per day and a sample standard deviation of 30 rooms
Part a
For this case the best point of estimate for the population variance would be:

Part b
The confidence interval for the population variance is given by the following formula:
The degrees of freedom are given by:
Since the Confidence is 0.90 or 90%, the significance
and
, the critical values for this case are:
And replacing into the formula for the interval we got:
Part c
Now we just take square root on both sides of the interval and we got:
Answer:
A) from the line of best fit, the approximately y-intercept is (0,1.8). This means without any practice, 1h.8 games are won.
B) slope: (5.6-1.8)/(2-0) = 1.9
y = 1.9x + 1.8
(Line of best fit)
x = 13,
y = 1.9(13) + 1.8 = 26.5
Predicted no. of games won after 13 months of practice is 26.5