A is the answer I got hope this helps !!
Answer:
See ecplanation below
Step-by-step explanation:
False.
On the Data analysis tool from excel we can conduct the following procedures:
Anova: Single Factor
Anova: Two factor with replication
Anova: Two factor without replication
Correlation
Covariance
Descriptive statistics
Exponential smoothing
F-test Two sample for Variances
Fourier analysis
Histogram
Moving Average
Random number generation
Rank and percentile
Regression
Sampling
t test: Paired two sample for means
t tes: Two sample assuming equal variances
t test: Two sample Assuming Unequal Variances
z test: Two sample for means
And as we can see we don't have an specific procedure just to obtain confidence interval for the difference of proportions. We need to remember that if we select a z test in excel, for example the output will contain the confidence associated to the parameter, but for this case is not too easy obtain a confidence interval for the difference of proportion like on a statistical software as (Minitab, R, SAS, etc) since all of these statistical softwares are elaborated in order to conduct all the possible statistical tests and confidence intervals for parameters of interest.
Answer:
no
Step-by-step explanation:
no they are not they are hard
Answer:
The rectangle is 3.2 cm by 12.6 cm
Step-by-step explanation:
See attached image for a diagram.
Choose <em>w</em> to represent the width because the length is described by referring to the width: it's 3 more than (add 3) triple (multiplied by 3) the width.
Length = 3w + 3
The diagonal forms two right triangles, each with leg = <em>w</em>, other leg = 3<em>w</em> + 3, hypotenuse = 13.
The Pythagorean Theorem says 
so
Now solve using the Quadratic Formula with 
.
The negative root makes no sense as a distance, so the width of the rectangle is 3.2 cm. The length is 3(3.2) + 3 = 12.6 cm.
Answer:
The expectation of the policy until the person reaches 61 is of -$4.
Step-by-step explanation:
We have these following probabilities:
0.954 probability of a loss of $50.
1 - 0.954 = 0.046 probability of "earning" 1000 - 50 = $950.
Find the expectation of the policy until the person reaches 61.
Each outcome multiplied by it's probability, so:
The expectation of the policy until the person reaches 61 is of -$4.
