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Confidence Intervals with Means Chapter 12 Section 2 What is the purpose of a confidence interval? To estimate an unknown population parameter In this case we will be estimating mean. Steps for doing a confidence interval: 1) Assumptions – 2) Calculate the interval 3) Write a statement about the interval in the context of the problem. Assumptions for z-inference • Have an SRS from population (or randomly assigned treatments) • s known • Normal (or approx. normal) distribution – Given – Large sample size Use only one of these methods to • Population is at least 10ncheck normality Formula: Standard deviation of Critical value statistic Confidence Interval : s x z * n statistic Margin of error Statement: (memorize!!) We are ________% confident that the true mean context is between ______ and ______. Example A sample of pulse rates of 40 women selected at random had a mean of 76.3 per minute. If the standard deviation of the population is 12.5 use a .95 confidence level to find a confidence interval for . Determining Sample Size You want to estimate the mean number of sentences in a magazine ad. How many magazine ads must be included in the sample if you want to be 95% confident that the sample mean is within one sentence of the population mean? (use s = 5.0) In a randomized comparative experiment on the effects of calcium on blood pressure, researchers divided 54 healthy, white males at random into two groups, takes calcium or placebo. The paper reports a mean seated systolic blood pressure of 114.9 with standard deviation of 9.3 for the placebo group. Assume systolic blood pressure is normally distributed. Find a 95% confidence interval for the true mean systolic blood pressure of the placebo group. Can you find a z-interval for this problem? Why or why not? Student’s t- distribution In many real-life situations, the population standard deviation is not known and it is often not practical to collect sample sizes of 30 or more. However, if the random variable is approximately normally distributed, the sampling distribution for x is a t-distribution. Student’s t- distribution • Developed by William Gosset • Continuous distribution • Unimodal, symmetrical, bell-shaped density curve • Above the horizontal axis • Area under the curve equals 1 • Based on degrees of freedom df = n - 1 Graph examples of t- curves vs standard normal curve How does the t-distributions compare to the standard normal distribution? • Shorter & more spread out • More area under the tails • As n increases, t-distributions become more like a standard normal distribution Steps for doing a confidence interval: 1) Assumptions – 2) Calculate the interval 3) Write a statement about the interval in the context of the problem. Assumptions for t-inference • Have an SRS from population (or randomly assigned treatments) • s unknown • Normal (or approx. normal) distribution – Given – Large sample size – Check graph of data Use only one of these methods to check normality Formula: Standard deviation of Standard error – Critical value statistic when you substitute s for s. Confidence Interval : s x t * n statistic Margin of error How to find t* Can also use invT on the calculator! • Use Table B for t distributions t* value with 5% at is above • Need Lookupper up confidence level bottom– & so 95% is below df on the sides • df = n – 1 invT(p,df) Find these t* 90% confidence when n = 5 95% confidence when n = 15 t* =2.132 t* =2.145 Statement: (memorize!!) We are ________% confident that the true mean context is between ______ and ______. CI & p-values deal with area in the tails Robust – is the area changed greatly when there is skewness • An inference procedure is ROBUST if the confidence level or p-value doesn’t change much if the normality assumption is violated. Since there is more area in the tails in tdistributions,can then, a distribution has • t-procedures beif used with some some skewness, tail area not skewness, as long the as there areisno greatly affected. outliers. • Larger n can have more skewness. In a randomized comparative experiment on the effects of calcium on blood pressure, researchers divided 54 healthy, white males at random into two groups, each person takes calcium or a placebo. The paper reports a mean seated systolic blood pressure of 114.9 with standard deviation of 9.3 for the placebo group. Assume systolic blood pressure is normally distributed. Find a 95% confidence interval for the true mean systolic blood pressure of the placebo group. Ex. 1) Find a 95% confidence interval for the true mean systolic blood pressure of the placebo group. Assumptions: • Have randomly assigned males to treatment • Systolic blood pressure is normally distributed (given). • s is unknown •Population is at least 270 males 9.3 114.9 2.056 (111.22, 118.58) 27 We are 95% confident that the true mean systolic blood pressure is between 111.22 and 118.58. Ex. 2) A medical researcher measured the pulse rate of a random sample of 20 adults and found a mean pulse rate of 72.69 beats per minute with a standard deviation of 3.86 beats per minute. Assume pulse rate is normally distributed. Compute a 95% confidence interval for the true mean pulse rates of adults. We are 95% confident that the true mean pulse rate of adults is between 70.883 & 74.497. (Be sure to include assumptions and Calculations!) Ex 2 continued) Another medical researcher claims that the true mean pulse rate for adults is 72 beats per minute. Does the evidence support or refute this? Explain. The 95% confidence interval contains the claim of 72 beats per minute. Therefore, there is no evidence to doubt the claim. Ex. 3) Consumer Reports tested 14 randomly selected brands of vanilla yogurt and found the following numbers of calories per serving: 160 200 220 230 120 180 140 130 170 190 80 120 100 170 Compute a 98% confidence interval for the average calorie content per serving of vanilla yogurt. We are 98% confident that the true mean calorie content per serving of vanilla yogurt is between 126.16 calories & 189.56 calories. Ex 3 continued) A diet guide claims that you will get 120 calories from a serving Note: confidence intervals tell us of vanilla yogurt. What does this if something is NOT EQUAL – evidence indicate? never less or greater than! Since 120 calories is not contained within the 98% confidence interval, the evidence suggest that the average calories per serving does not equal 120 calories. Find a sample size: • If a certain margin of error is wanted, then to find the sample size necessary for that margin of error use: s m z * n Always round up to the nearest person! Ex 4) The heights of MHS male students is normally distributed with s = 2.5 inches. How large a sample is necessary to be accurate within + .75 inches with a 95% confidence interval? n = 43 Some Cautions: • The data MUST be a SRS from the population (or randomly assigned treatment) • The formula is not correct for more complex sampling designs, i.e., stratified, etc. • No way to correct for bias in data Cautions continued: • Outliers can have a large effect on confidence interval • Must know s to do a z-interval – which is unrealistic in practice