Lesson SH1-SH2
SH1-SH2 Confidence intervals for a mean from large samples Quiz: AQA Further Maths, Unit 4
20 questions
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Lesson SH1-SH2, Confidence intervals for a mean from large samples: 20 multiple choice questions for the AQA Further Maths (7367), Unit 4: Optional application 2: statistics, written with Revision Ninja.
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The 20 questions
-
For a normal population with known variance sigma^2, which expression gives the symmetric 95% confidence interval for the population mean from a sample of n observations with mean xbar?
- xbar ± 1.645 × sigma/sqrt(n)
- xbar ± 1.96 × sigma^2/n
- xbar ± 1.96 × sigma × sqrt(n)
- xbar ± 1.96 × sigma/sqrt(n)
-
What is the standard error of the sample mean for n independent observations from a population with standard deviation sigma?
- sqrt(sigma/n)
- sigma^2/sqrt(n)
- sigma/n
- sigma/sqrt(n)
-
Which z value gives a symmetric 99% confidence interval for a normal mean, using the standard normal distribution?
- 2.326
- 1.645
- 1.960
- 2.576
-
Which z value gives a symmetric 90% confidence interval for a normal mean?
- 1.282
- 2.576
- 1.645
- 1.960
-
What does the confidence level of 95% mean for a symmetric confidence interval?
- The sample mean lies inside the interval with probability 0.95 after each new sample is taken
- There is a 95% probability that the true mean lies inside this particular calculated interval
- About 95% of the individual data values lie inside the calculated interval
- In repeated sampling, about 95% of intervals constructed this way would contain the true population mean
-
A sample of n = 36 is taken from a normal population with known sigma = 6. The sample mean is 50. What is the 95% confidence interval for the population mean?
- (48.04, 51.96)
- (48.04, 52.96)
- (49.00, 51.00)
- (44.12, 55.88)
-
A sample of n = 25 from a normal population with known sigma = 2 has mean 17.3. What is the symmetric 99% confidence interval for the population mean, to 2 decimal places?
- (16.27, 18.33)
- (15.97, 18.63)
- (16.52, 18.08)
- (17.30, 18.70)
-
A sample of size n is multiplied by four, with sigma and the confidence level unchanged. How does the width of the symmetric confidence interval for the mean change?
- It halves, because the width is proportional to 1/sqrt(n)
- It is unchanged, because the width depends only on sigma and the confidence level
- It quadruples, because the width is proportional to n
- It doubles, because the width is proportional to sqrt(n)
-
A normal population has known sigma = 4.5. What is the smallest sample size for a symmetric 95% confidence interval for the mean to have total width at most 2?
- 39
- 78
- 156
- 77
-
A sample of n = 100 from a population with unknown variance has mean 24.6 and standard deviation 5.2. Using the large-sample method, what is the approximate symmetric 95% confidence interval for the mean?
- (14.41, 34.79)
- (23.26, 25.94)
- (23.58, 25.62)
- (24.08, 25.12)
-
Why is the sample standard deviation s used in place of sigma when constructing a large-sample confidence interval for a mean?
- The t-distribution must always be used instead of the normal distribution when sigma is unknown
- s is always larger than sigma, so the interval it gives is wider and therefore safer
- For large n, s is a good estimate of sigma, so the normal approximation with z values remains reasonable
- The central limit theorem makes the sample standard deviation exactly equal to sigma for any sample
-
A symmetric 95% confidence interval for a population mean is (12.1, 15.9). What is the sample mean used to construct it?
- 14.0
- 3.8
- 15.9
- 13.0
-
A symmetric 95% confidence interval for a population mean is (12.1, 15.9). Assuming the z-based method, what is the standard error used?
- Approximately 1.900
- Approximately 0.950
- Approximately 0.969
- Approximately 3.724
-
Keeping the data fixed, how does a symmetric 95% confidence interval for a mean change when the confidence level is raised to 99%?
- It moves to a new centre, because the sample mean changes with the confidence level
- It becomes wider, because the z value rises from 1.96 to 2.576
- It becomes narrower, because the z value falls from 1.96 to 1.645
- It is unchanged, because the same sample data are used
-
A sample of n = 16 from a normal population with known sigma gives the 95% confidence interval (42.0, 48.0) for the mean. What is sigma, to 3 significant figures?
- 3.06
- 12.2
- 1.53
- 6.12
-
A normal population has known sigma = 3. What is the smallest sample size needed for a symmetric 95% confidence interval for the mean to have margin of error at most 0.5?
- 138
- 277
- 139
- 35
-
A symmetric 90% confidence interval is to be found for the mean of a normal population with known sigma = 10, using n = 25 observations with sample mean 60. What is the interval?
- (56.08, 63.92)
- (53.42, 66.58)
- (58.00, 62.00)
- (56.71, 63.29)
-
Which statement about a symmetric 95% confidence interval is correct?
- Before the sample is taken, there is a 95% probability that the random interval will contain the true population mean
- After the sample is taken, there is a 95% probability that the true mean lies within this specific interval
- The sample mean will lie inside the calculated interval for 95% of future samples
- 95% of the individual observations in the sample lie inside the calculated interval
-
A student has n = 12 normal observations with unknown variance. The student uses the sample standard deviation s in a z-based 95% interval. What is the best criticism of this method?
- The z-based interval is too narrow, since the t-distribution with 11 degrees of freedom (critical value about 2.201) should be used
- Using s always gives a narrower interval than using the unknown sigma would give
- The critical value should be 2.576 because s is only a sample estimate of sigma
- The z-based interval is valid because n = 12 is large enough for the central limit theorem to apply
-
A sample of n = 400 from a population with unknown variance has mean 50 and standard deviation 8. What is the approximate symmetric 95% confidence interval for the mean?
- (48.43, 51.57)
- (49.61, 50.39)
- (42.16, 57.84)
- (49.22, 50.78)
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