Please help me solve this problem

Answer:

3

Step-by-step explanation:

    6 cups  require 2 cups

    9 cups require-------x

Cross multiplication

9x2 = 6x

18 = 6x

x= 3

 Another way to think about:

6 + half of 6 = 9

   Then

2+ and half of 2 = 3

       6 is 3 times more than 2

        9 is 3 times bigger than 3

Answer:

a. non response bias

This is one of the usually cause when we use a non-random sample, sinc the probability of selection for all the individuals on the population is not the same when we use this, we are comitting non response bias since we are not taking in count some people in the possible target sample.

Nonresponse bias is "the bias that results when respondents differ in meaningful ways from nonrespondents. Nonresponse is often problem with mail surveys, where the response rate can be very low".

Step-by-step explanation:

Random sample

For this method we need the following two conditions:

(1) "Every element in our population has a nonzero probability of being selected as part of the sample."

(2)" We have accurate knowledge of this probability, known as the inclusion probability, for each element in the sampling frame".

Non random sample

It's the opposite of random sample and we have these problems associated:

(1) "It is relatively unusual to have a sampling frame available to you when you’re conducting market studies".

(2) "Ensuring that every individual in a population has a nonzero probability of being selected is just as difficult to accomplish; knowing every sampling unit’s exact inclusion probability is even more difficult. The individuals that cannot be selected as part of a sample are generally referred to as excluded units".

Assuming the following options:

a. non response bias

This is one of the usually cause when we use a non-random sample, sinc the probability of selection for all the individuals on the population is not the same when we use this, we are comitting non response bias since we are not taking in count some people in the possible target sample.

Nonresponse bias is "the bias that results when respondents differ in meaningful ways from nonrespondents. Nonresponse is often problem with mail surveys, where the response rate can be very low".

b. parameter

False we are looking for a cause related to non random sample. The parameter is just a value that we want to find but is not a cause related to the non random sample.

c. statistics

False, we can associate a cause of non random sample with the statistics. The term "statistics" is a big concept that involves a lot of methods and ways to analyze information, and is not the correct cause associated to the non-random sample.

d. population

False, we can associate the population as a cause of the non random sample. We use sampling methods in order to estimate some population parameters. But the population is not a cause of the non-random sample.

Answer:

Distribution will get taller and SD will decrease.

Step-by-step explanation:

Sample Size and Standard Deviation:

In a t-distribution, sample size and standard deviation are inversely related.

A larger sample size results in decreased standard deviation and a smaller sample size will result in increased standard deviation.

Sample Size and Shape of t-distribution:

As we increase the sample size, the corresponding degree of freedom increases which causes the t-distribution to like normal distribution.  With a considerably larger sample size, the t-distribution and normal distribution are almost identical.

Degree of freedom = n - 1

Where n is the sample size.

The shape of the t-distribution becomes more taller and less spread out as the sample size is increased

Refer to the attached graphs, where the shape of a t-distribution is shown with respect to degrees of freedom and also t-distribution is compared with normal distribution.

We can clearly notice that as the degree of freedom increases, the shape of the t-distribution becomes taller and narrower which means more data at the center rather than at the tails.

Also notice that as the degree of freedom increases, the shape of the t-distribution approaches normal distribution.

Final answer:

In a t-distribution, as the sample size increases, the distribution becomes 'shorter', and the standard deviation decreases following the law of large numbers. The increased sample size reduces variability and introduces less deviation from the mean.

Explanation:

As the sample size increases for a t-distribution, the distribution tends to approach a normal distribution shape, which means the distribution will get 'shorter'. Additionally, the standard deviation (SD) would generally decrease as the sample size increases. This is due to the fact that when sample size increases, a smaller variability is introduced, hence less deviation from the mean.

To illustrate, imagine rolling a dice. If you roll it a few times, you may end up with quite a bit of variation. If you roll it a hundred times, however, the numbers should average out closer to the expected value (3.5 for a six-sided dice), and the standard deviation (a measure of variability) would decrease.

In conclusion, when the sample size increases, a t-distribution will get 'shorter' and SD will decrease. This concept is often referred as the law of large numbers.

Learn more about t-distribution here:

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