1. A data set consists of the ages at death

Nettie Potts 2022-03-03 Answered
1. A data set consists of the ages at death for each of the 41 past presidents of United States.
2. Is this set of measurement a population or a sample?
a. What is the variable being measured?
b. What measurement scale is appropriate for the data?
You can still ask an expert for help

Expert Community at Your Service

  • Live experts 24/7
  • Questions are typically answered in as fast as 30 minutes
  • Personalized clear answers
Learn more

Solve your problem for the price of one coffee

  • Available 24/7
  • Math expert for every subject
  • Pay only if we can solve it
Ask Question

Expert Answer

asserena3wx
Answered 2022-03-04 Author has 7 answers
In statistics, various types of variables are studied. There are two types of variables that are mainly focused in statistics. These are:
Qualitative variable
Quantitative variable.
On the other hand, there are 4 types of scales that belong to above 2 variables. These are:
Ordinal
Interval
Ratio
Nominal
These could be defined as:
Quantitative variable : As the name suggests, those variables which have some numeric value assigned to it are classified as quantitative variable. It is discrete or continuous. For example, number of students scoring marks in 0 - 20, 20 - 40, 40 - 60, 60- 80, 80 - 100 intervals.
Qualitative variables : Such kind of variables are also known as categorical variable. The are further divided into nominal and ordinal variable. It comprises of data subdivided into different categories or groups which has no numerical value. For example, hot and cold, insured divided on the basis of no claims, 1 claim, more than 1 claim.
And,
In the interval level of measurement, the difference between the observations has a significant meaning. The interval level of measurement has no absolute zero.
A nominal level of measurement is defined as a measure that is used to label the variables.
The ratio level of measurement has similar properties to the interval level of measurement and the natural zero exists for this type of scale.
An ordinal level of measurement is used to compare the variables where the order of the data matters. It is used to divide the data based on ranking.
a). The data contains about all 38 deceased U.S presidents. Therefore, the set of measurements is a population.
b). The variable being measured is age at death of president.
c). The measurement of scale is ratio scale of measurement.

We have step-by-step solutions for your answer!

Expert Community at Your Service

  • Live experts 24/7
  • Questions are typically answered in as fast as 30 minutes
  • Personalized clear answers
Learn more

You might be interested in

asked 2022-05-14
Assuming that i have seed bag sizes of 1kg, 2 kg, and 5kg. And my clients typically have a land size between 0.25 and 5 acres and will plant 10kgs per acre.
What formualar can i use to calculate for each client the number of 5kg, 2kg and 1kg seed bags they need for planting. In the calculation, i want to try to assign the larger bags first while avoiding to assign half bags to a client as much as possible.
asked 2022-05-15
so my task is to find out if the random variables defined by X n ( t ) = n ( t ) n with t [ 0 , 1 ] converges almost surely against another random variable X in the probability space ( [ 0 , 1 ] , B [ 0 , 1 ] , λ [ 0 , 1 ] ). In a first step I tried to find X by calculating lim n X n ( t ), which gives me the following:
X = { 0 , 0 t < 1 ± , t = 1
So my question now is if it's even possible for this sequence of random variables to converge at all. I would say no but I'm not sure though cause 1 is a null set for the Lebesgue measure. If I'm correct is it, therefore, ok to conclude that any sequence of random variables with no unique limit function doesn't converge for any probability measure?
asked 2022-06-28
To calculate the random error in a set of measurements this is what I would do.

1. Get the standard deviation of the measurements:
σ = 1 N 1 Σ i = 1 N ( x i x ¯ ) 2
Where N is the number of repeats, x i is the value of each sample, x ¯ is the mean, and σ is the standard deviation.
2. The standard error of the mean:
s x ¯ = σ N
3. Obtain the random error using a t distribution:
ε r n d = ± t N 1 s x ¯

The problem is, if I have a measurement with a single reading of a given value, this method for random error calculation is clearly no longer applicable.
Therefore, how would you go about calculating the random error in a for a sample set where N=1? Is that even possible?
asked 2022-04-12
At work, there is a statistical process going on, which I feel is probably mathematically incorrect but can't quite put my finger on what is wrong:
They are totalling up the number of hours people work per week (in minimum units of 15 minutes), and then producing averages for the whole department per week. Obviously, the results come out to be non-integer numbers of hours with a long number of decimals.
Then, they are judging the result of certain productivity-boosting techniques and displaying the findings in "minutes gained/lost"...in some cases producing productivity gains of as little as a minute or two minutes per week.
So to summarise, they are calculating units of quarters of an hour, but then presenting the average productivity gains in minutes...is this presuming an accuracy which is not present in the initial measurement? I think it is, but don't know how to argue it to my boss.
asked 2022-05-14
Let μ be a positive Borel measure on (0,1) and g L 2 ( μ ) be such that g 2 = 1.. Then does there exist f C 0 ( ( 0 , 1 ) ) such that ( 0 , 1 ) | g | 2 ( f 1 )   d μ = 0   ?
If we can show that the above integral is zero iff f 1 = 0 almost everywhere then by continuity of f we have f 1 on (0,1). But then f C 0 ( ( 0 , 1 ) ) for otherwise it approaches to 0 near the endpoints which is not the case.
asked 2022-04-21
The length of a rod was measured eight times. The measurements in centimeters, in the order they were taken, were 21.20, 21.22, 21.25, 21.26, 21.28, 21.30, 21.32, 21.35.
a) Do these measurements appear to be a random sample from a population of possible measurements? Why or why not?
b) Is it possible to estimate the uncertainty in these measurements? Explain.
asked 2022-03-15
A student is performing measurements in the chemistry laboratory and recording the results in a lab report. The student performs the experiment four times and records the mean x of the four measurement trials. Suppose that the chemistry teacher has found that ? = 12 milligrams from previous similar experiments.
(a) What is the standard deviation of the student's mean result? (That is, if the student kept on making four measurements and averaging them, what would be the standard deviation of all the x values?)
mg
(b) How many times must the student perform the measurement to reduce the standard deviation of x to 2?
n =
(c) Explain to someone who knows no statistics the advantage of reporting the average of several measurements rather than the result of a single measurement.
-The average of several measurements will always be an unbiased estimate of the mean.
-The average of several measurements is more likely than a single measurement to be close to the mean.
-The result of a single measurement will never be close to the mean.
-Taking several measurements reduces the likelihood of reporting error.

New questions