This is a False statement
In a normal distribution at 95% confidence interval from sample mean we add or subtract 1.96 times the standard error to calculate the confidence interval of the population mean on the basis of sample mean and the sample size but it doesn't say anything about the sample . Hence this statement is false.
In a normal distribution, if I take the mean value and I add or subtract 1.96...
Question 5 In a normal distribution, if l take the mean value and I add or subtract 1.96 times the standard error of the mean SEM), I would obtain 99.7% of my sample a. True b. False c. We don't have enough information d. None of the above
10. Assume that 20 people take a math test, which is not enough for a normal distribution to form. If Conrad scores three standard deviations above the mean, what percentile is he? 1. 75.0% 2. 88.5% 3. 95.0% 4. 99.7% 5. Not enough information to determine. ________________________________________ 11. Assume that 20 people take a math test, which is not enough for a normal distribution to form. If Sarah scores at the median, what percentile is she? 1. 34% 2. 50%...
2. Suppose we have a Normal distribution with mean 35 and standard deviation 4. Take a few a. minutes to draw this curve very neatly and accurately. Reference the document "How to Draw a Normal Curve" in this assessment. Use a separate sheet of paper, or add extra space here, and use a straightedge to draw an axis. b. Label your curve from part a with the 68-95-99.7 Rule. c. If we randomly select a value from this Normal model...
The time required for Dr. B's students to complete the Statistics Exam is approximately normally distributed with a mean of 40.4 minutes and a standard deviation of 2.2 minutes. Let X be the random variable "the time required for Dr. B's students to complete the Statistics Exam." 6. With the above setting what time marks the 90th percentile? A. 37.562 minutes B. 37.584 minutes C. 43.238 minutes D. 43.216 minutes E. None of the above 7. Which of the following...
1. Select all true statements about sample mean and sample median. A) When the population distribution is skewed, sample mean is biased but sample median is an unbiased estimator of population mean. B) When the population distribution is symmetric, both mean and sample median are unbiased estimators of population mean. C) Sampling distribution of sample mean has a smaller standard error than sample median when population distribution is normal. D) Both mean and median are unbiased estimators of population mean...
R problem 1: The reason that the t distribution is important is that the sampling distribution of the standardized sample mean is different depending on whether we use the true population standard deviation or one estimated from sample data. This problem addresses this issue. 1. Generate 10,000 samples of size n- 4 from a normal distribution with mean 100 and standard deviation σ = 12, Find the 10,000 sample means and find the 10,000 sample standard deviations. What are the...
14. TRUE or FALSE? If X is any normal distribution, then about 95% of all observations from X will fall within two standard deviations of the mean. 15. TRUE or FALSE? The normal quantile value 0-1(0.025) = -1.96. 16. TRUE or FALSE? If X ~ Nor(u, o?), then Pr(-1 < X-< 1) = 0.6826.
Suppose that we take a sample of 25 observations from a Normal distribution with a mean of 10 and a standard deviation of 4. Write 'X-bar' for the average of the sample. What is the probability that X-bar is less than 12? 0.9938 0.6915 0.3085 0.9772 0.0062
Which of the following statements about the sampling distribution of the sample mean, x-bar, is not true? The distribution is normal regardless of the shape of the population distribution, as long as the sample size, n, is large enough. The distribution is normal regardless of the sample size, as long as the population distribution is normal. The distribution's mean is the same as the population mean. The distribution's standard deviation is smaller than the population standard deviation. All of the...
Question 183 pts In a normal distribution, what percentage of sample observations fall between the mean and .71 standard deviations above or below the mean? 1.96% 76.11% 26.11% 13.6%