Age 0-14 number of people= 206,423

Age 15-34 number of people= 265,778
Age 35-54 number of people= 308,946
Age 55-74 number of people= 159,092
Age over 74 number of people= 69,264

1)Classify the data in the table.
A)positively skewed
B)negatively skewed
C)normally distributed
D)discrete distribution
My first choice was C but I went with A instead.

2)For 2000 patients, a blood-clotting time was normally distributed with a mean of 8 seconds. What percent had blood-clotting times between 5 and 11 seconds?
A)68%
B)34%
C)49/5%
D)47/5%
I chose A

3)During a sale, 1/6 of the CD prices are reduced. Find the probability that 2 of 4 randomly-selected CDs have reduced prices?
A)5/36
B)25/1296
C)25/216
D)5/216
I don't know

4)A music teacher wants to determine the music performances of students. A survey of which group would produce a random sample?
A)students in the school band
B)students attendeing the annual jazz concert
C)students in every odd-numbered homeroom
D)every other player on the baseball roster
I chose B

5)In an election poll, 56% of 400 voters chose a certain canidate. Find the margin of sampling error.
A)5%
B)2%
C)4%
D)7%
I chose A

Please only post your questions once. Repeating posts will not get a quicker response. In addition, it wastes our time looking over reposts that have already been answered in a previous post. Thank you.

See my response to your later post.

1) Classify the data in the table: The data in the table represents the number of people in each age group. To classify the data, you can analyze the distribution shape. In this case, you mentioned that your first choice was option C (normally distributed), but you settled on option A (positively skewed) instead.

To determine if the data is positively skewed, you can observe that the younger age groups (0-14 and 15-34) have higher numbers, while the older age groups (55-74 and over 74) have lower numbers. This indicates a higher concentration of individuals in the younger age groups and a decreasing trend as the age increases. Therefore, the data is positively skewed.

2) For a normally distributed sample with a mean of 8 seconds and 2000 patients, to find the percent of patients with blood-clotting times between 5 and 11 seconds, you can use the empirical rule (also known as the 68-95-99.7 rule) which states that roughly 68% of the data falls within one standard deviation of the mean for a normal distribution.

In this case, you want to find the percentage within two standard deviations of the mean, which would account for 95% of the data. Since the blood clotting times are normally distributed with a mean of 8 seconds, you need to calculate the standard deviation. With this information, you can determine the percentage of patients with blood-clotting times between 5 and 11 seconds.

3) For the probability that exactly 2 of the 4 randomly-selected CDs have reduced prices, you can use the concept of combinations. There are 4 CDs in total, and 1/6 of them have reduced prices. To calculate the probability, you need to calculate the number of ways to select 2 CDs with reduced prices out of the total 4 CDs.

The formula to calculate combinations is C(n, r) = n! / (r! * (n - r)!), where n is the total number of items and r is the number of items to be chosen.

4) To produce a random sample, you want to ensure that every member of the population has an equal chance of being selected. In this case, the music teacher wants to determine the music performances of students. The option that would produce a random sample is to select students in every odd-numbered homeroom, as every student has an equal chance of being selected.

5) To find the margin of sampling error for an election poll with a certain candidate chosen by 56% of 400 voters, you need to calculate the standard error. The margin of sampling error is often calculated using a formula that involves the sample size and the percentage of people in the sample who chose a certain candidate.

The formula is: margin of error = critical value * (sample standard deviation / sqrt(sample size)), where the critical value depends on the chosen confidence level (e.g., 95% confidence level is often associated with a critical value of 1.96). The sample size is 400, and the percentage that chose a certain candidate is 56%, so you can calculate the margin of sampling error using this information.