Answer:
Step-by-step explanation:
We have the standard deviation for the sample, so we use the t-distribution to solve this question.
The first step to solve this problem is finding how many degrees of freedom, we have. This is the sample size subtracted by 1. So
df = 20 - 1 = 19
99% confidence interval
Now, we have to find a value of T, which is found looking at the t table, with 19 degrees of freedom(y-axis) and a confidence level of 
. So we have T = 2.861.
The margin of error is:
In which s is the standard deviation of the sample and n is the size of the sample.
The format of the confidence interval is:
In which 
is the sample mean
So
Answer: 2( x - 13 ) ≥ 17
Step-by-step explanation:
Answer:
Well, these simulation are based on the statistics (lognormal-distributed PE, χ²-distributed s²). If you believe that only the ‘gold-standard’ of subject-simulations are valid, we can misuse the function sampleN.scABEL.sdsims() – only for the 3- and 4-period full replicates and the partial replicate:
# define a reg_const where all scaling conditions are ‘switched off’
abe <- reg_const("USER", r_const = NA, CVswitch = Inf,
CVcap = Inf, pe_constr = FALSE)
CV <- 0.4
2x2x4 0.05 0.4 0.4 0.95 0.8 1.25 34 0.819161 0.8
Since the sample sizes obtained by all simulations match the exact method, we can be confident that it is correct. As usual with a higher number of simulations power gets closer to the exact value.
Step-by-step explanation:
Answer:
6 square units
Step-by-step explanation:
In oder to do this, you need graph paper to make it easier and then mark your graph paper with the quadrants.
I got 3 unites for the height and 4 units for the base
4 x 3 = 12 square units
however the formula for a triangle is Ab/2
so divide 12/2 = 6
So its 6 square units
Answer:
193 seconds
Step-by-step explanation:
For this problem you'll have to divide so do -145÷-0.75 and your answer will be 193 seconds
