Answer:
Exp Date: 1/17/2017
Exp Time: 4:00am
Prep Date: 12/3/2016
Prep Time: 4:00am
Initials: 12/7/2016
Step-by-step explanation:
A well-detailed version of the question has been uploaded in form of an image for easier understand.
Looking at the question, it was said that she received her store order on 12/3/2016 at 4am, this implies that the prep date and time are 12/3/2016 and 4am respectively. Also, it was said that the expiration date was printed on the product and it is 1/17/2017. Obviously, the expiration time would also be 4am because it was prepared at 4am and if we calculate in. 24hours we would get 4am at the expiration date as well. Lastly, we were told she opened the product she received on 12/7/2016 which is the initial date the product was used. From all these we can deduce the following:
Exp Date: 1/17/2017
Exp Time: 4:00am
Prep Date: 12/3/2016
Prep Time: 4:00am
Initials: 12/7/2016
Answer:
One-way ANOVA
Step-by-step explanation:
One-way ANOVA(analysis of variance) a testing method in statistics that is used to compare the means of two or more independent samples, to check if the differences are statistically significant.
In this case, we have three groups which their various reaction time to caffeine is to be tested using the same testing method (amount of caffeine). Hence the appropriate test to use here is the one-way ANOVA
<span>Mario has drawn a plan of his bedroom on 1 cm square paper. His en-suite shower cubicle measure. 1m x1m, give the scale of his drawing
as ratio _ 1 cm__ : __1m_.
What are the actual dimension of his bed __1__ m x _1_ m</span>
Answer:
Since the name indicates Minimum Variance Unbiased Estimator-first of all it is a parameter estimator. Secondly, it is an unbiased estimator so that the sample is carried out randomly. I.e. whenever a sample is chosen, there is no personal bias.
Then we can consider more than one sample-based unbiased estimator but sometimes they can vary in variation. But we have always intended to select an estimator that has minimal variance.
Therefore if the unbiased estimator has minimal variation between all unbiased class estimators then it is known as a good estimator.
The advantage of MVUE is that it is impartial and has a minimal variance of all unbiased estimators amongst the groups.
At times we get an estimator such as MLE which is not unbiased because the sample can be personally biased. Now let us assume an instructor needs to find the lowest marks in a physics class. Presume an instructor picks a sample and interprets the lowest possible marks.
Again the mistake could be that the instructor may choose his favorite sample learners because the sample might not be selected randomly. Therefore it is important to select an unbiased estimate with a minimum variance.
<span>Randomly generate an integer from 1 to 7 two times, and the probability is 1/7 ^2
This is the </span><span>statement that best describes the use of a simulation to predict the probability that two randomly chosen people will both have their birthdays on a Monday.
There are 7 days in a week, so there are 7 choices but only 1 Monday. So, 1/7 is the probability that a person's birthday falls on a Monday.
1st person asked will have 1/7 probability.
2nd person asked will also have 1/7 probability
So, (1/7)</span>² is the probability that both persons will have their birthdays on a Monday.
