What is the difference between parameters and statistics? 2. Does statistical process control inspect all the items produced after they are finished? 3. The inspector samples five circuit boards at regular intervals and finds the mean solder quality score x for these five boards. Do we expect x to be exactly 100 if the soldering process is functioning properly? 4. If the quality of individual boards varies according to a normal distribution with mean µ = 100 and standard deviation σ = 4 , what will be the distribution of the sample averages, x ? (Recall the sample size is n = 5.) 5. In general, is the mean of several observations more or less variable than single observations from a population? Explain. 6. The distribution of call lengths to a call center is strongly skewed. What does the Central Limit Theorem say about the distribution of the mean call length x from large samples of calls?

1. The parameter refers to the entire population

The statistics refers to a sample

2. only a sample will be inspected

3. No only 99.7%

4. A student t distribution with spread = σ/√n

5. The mean is less variable than single observations from the population

6. The distribution of the mean call length x becomes approximately normal distributed

Step-by-step explanation:

1. The parameter refers to numbers that summarize the data of the entire population while;

The statistics refers to the numbers that summarize the data for a subset of the population or of a sample

2. No only a sample will be inspected

3. No he expects 99.7% to function within three standard deviations of the mean

4. The distribution of the sample average will be the student t distribution curve with spread = σ/√n

5, The mean comprises a collection of variables from the sample, hence it is less variable than single observations from the population

6. According to the Central Limit Theorem, the distribution of the mean call length x from large samples of calls becomes more and more approximately normal as the size of the sample approaches that of the population.

1; 35 is the ratio

step-by-step explanation:

your exact question is kind of difficult to understand, so maybe an example will explain what you're supposed to do? i'll work through the first problem on the worksheet.

suppose you have a tray of 652 brownies, and you have 5 friends that you want to feed without picking favorites. how many brownies can you dole out to each of your friends in equal amounts? how many will be left over for you to eat?

what you're doing here is finding a way to arrange the number 652 as the sum of integer multiple of 5 and some remainder:

here ("q" for quotient) is the number of brownies each of your friends get, and is the remainder. that's the basic idea behind division.

we break up the number 652 into parts so that the leading digit stands on its own:

652 = 600 + 52

first we check if it's possible to hand out exactly 100 brownies to each friend. with 5 friends, this means we want to know if we can take out 500 brownies from the tray. we can do this 1 time because we have 600 brownies to take from, and when we do that we're left with 100 + 52 brownies to divvy up. so we know that

652 = 1*500 + 152

next we want to know if it's possible to hand out exactly 10 brownies per friend. if we can, we have to remove 50 brownies from the tray each time until we can't. we have 152 brownies left, and we know that 3(50) = 150, so

152 = 3*50 + 2

now we have 2 brownies left in the tray. is it possible to hand 1 out to each of your 5 friends? no, you'd need a minimum of 5 brownies to do that. so the last 2 are yours.

putting everything together, we found that

652 = 1*500 + 3*50 + 2

and we can rearrange this to write

652 = 5*100 + 5*30 + 2

652 = 5(100 + 30) + 2

652 = 5*130 + 2

so and .

you might be more accustomed to the table depicting the algorithm. that's just a compact way of organizing what we've done above. you can consult the image i've attached below.