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Suppose researchers are interested in estimating the mean height of a certain population of males. A sample of 410 males from this population yielded a sample mean height of 192.1 cm, with an associated 95% confidence interval of 19"]..3 to 1?2.9 cm. Suppose the assumptions of the procedure they' used were met. Of the following options. which one is the best interpretation of that interval? 0 We can be 95% confident that the true mean height for males in this population lies between 1?1.3 and 192.9 cm. 0 95% of this population of males have heights between 1?1.3 and 192.9 cm. 0 We can be 95% confident that the sample mean height of the 410 males lies between 1?1.3 and 1332.9 cm. 0 In repeated sampling, 95% of the 95% confidence intervals calculated in this manner will capture the mean height of the males in the sample. Consider the 4 normal quantile-quantile plots given in the image. One of these illustrates a distribution that is skewed to the left. Which one? A B 0.8 0 Sample Quantiles Sample Quantiles -3 -2 -2 2 2 -1 2 Theoretical Quantiles Theoretical Quantiles C D 50 4.0 Sample Quantiles Sample Quantiles 2.0 2 2 2 Theoretical Quantiles Theoretical Quantiles OA OB Oc ODWhich of the following statements are true? There may be more than one correct statement; select all that are true. ()a) All else being equal, a 99% confidence interval for the population mean is narrower than the corresponding 95% confidence interval. (b) If two events A and Bare independent, then they cannot both occur on the same trial. (c) If Z is a standard normal random variable, then P(Z = 0) = 0.5. (d) The sample variance can never be negative.Which of the following statements are true? There may be more than one correct statement; select all that are true. ()a) All else being equal, a 99% confidence interval for the population mean is narrower than the corresponding 95% confidence interval. (b) If two events A and Bare independent, then they cannot both occur on the same trial. (c) If Z is a standard normal random variable, then P(Z = 0) = 0.5. (d) The sample variance can never be negative