Chapter 2 Statistical Inference  Estimation -Confidence interval estimation for mean and proportion -Determining sample size  Hypothesis Testing -Test for one and two means -Test for one and two proportions

Statistical Inference Statistical inference is a process of drawing an inference about the data statistically. It concerned in making conclusion about the characteristics of a population based on information contained in a sample. Since populations are characterized by numerical descriptive measures called parameters, therefore, statistical inference is concerned in making inferences about population parameters.

ESTIMATION In estimation, there are two terms that firstly, should be understand. The two terms involved in estimation are estimator and estimate. An estimate of a population parameter may be expressed in two ways: point estimate and interval estimate.

 Point Estimate A point estimate of a population parameter is a single value of a statistic. For example, the sample mean is a point estimate of the population mean μ. Similarly, the sample proportion is a point estimate of the population proportion p.

 Interval estimate An interval estimate is defined by two numbers, between which a population parameter is said to lie. For example, a < < b is an interval estimate of the population mean μ. It indicates that the population mean is greater than a but less than b.

 Point estimators Choosing the right point estimators to estimate a parameter depends on the properties of the estimators it selves. There are four properties of the estimators that need to be satisfied in which it is considered as best linear unbiased estimators. The properties are:  Unbiased  Consistent  Efficient  Sufficient

 Confidence Interval A range of values constructed from the sample data. So that the population parameter is likely to occur within that range at a specified probability. Specified probability is called the level of confidence. States how much confidence we have that this interval contains the true population parameter. The confidence level is denoted by Example :- 95% level of confidence would mean that if 100 confidence intervals were constructed, each based on the different sample from the same population, we would expect 95 of the intervals to contain the population mean.

To compute a confidence interval, we will consider two situations: i.We use sample data to estimate, with and the population standard deviation is known. ii.We use sample data to estimate, with and the population standard deviation is unknown. In this case, we substitute the sample standard deviation (s) for the population standard deviation

Example 2.1: Find 95% confidence interval for a population mean for these values : a) b)

a) 1 st Step: 2 nd Step: Find from table page rd Step: Use formula. 95% confidence interval of mean lies in between to

Example 2.2 : The mean and standard deviation of the maximum loads supported by sample of 60 cables are given tons and 0.73 tons. Find 95% confidence interval of the mean of the maximum loads all cables produced by company.

Example 2.3: The brightness of a television picture tube can be evaluated by measuring the amount of current required to achieve a particular brightness level. A random sample of 10 tubes indicated a sample mean 317.2microamps and a sample standard deviation is 15.7microamps. Find (in microamps) a 99% confidence interval estimate for mean current required to achieve a particular brightness level.

Solution: For 99% CI: From t normal distribution table:

Hence 99% CI Thus, we are 99% confident that the mean current required to achieve a particular brightness level is between and

Exercise 2.1: Taking a random sample of 35 individuals waiting to be serviced by the teller, we find that the mean waiting time was 22.0 min and the standard deviation was 8.0 min. Using a 90% confidence level, estimate the mean waiting time for all individuals waiting in the service line. Answer : [ , ]

Confidence Interval Estimates for the differences between two population mean, i) Variance and are known ii) If the population variances, and are unknown, then the following tables shows the different formulas that may be used depending on the sample sizes and the assumption on the population variances.

Equality of variances, when are unknown Sample size

Example 2.3: Two machines are used to fill plastic bottles with liquid laundry detergent. The standard deviations of fill volume are known to be and fluid ounce for the two machines, respectively. Two random samples of bottles from the machine 1 and bottles from machine 2 are selected, and the sample means fill volume are and fluid ounces. Construct a 90% confidence interval on the mean difference in fill volumes. Interpret the results. For 90% CI

Solution: We are 90% confidence that the mean difference to fill volumes lies between and fluid ounces.

Exercise 2.2: 17 male undergraduate students and 20 female undergraduate students are randomly selected from faculty of mechanical engineering. Result for test 2 SSM 3763 shown the following data: Assume that both population are normally distributed and have equal population variances. Construct a 95% confidence interval for the difference in the two means. Answer : [1.3217, ]

Example 2.4: According to a poll, 40% of working women says that they feel stress in working. The poll was based on a randomly selected of 1502 working women aged 30 and above. Construct a 95% confidence interval for the corresponding population proportion.

Solution: Let p be the proportion of all working women age 30 and above, who have a limited amount of time to relax, and let pˆ be the corresponding sample proportion. From the given information, n = 1502, pˆ = 0.40, qˆ =1− pˆ = 1 – 0.40 = 0.60 Hence, 95% CI : Thus, we can state with 95% confidence that the proportion of all working women aged 30 and above who have a limited amount of time to relax is between 37.5% and 42.5%.

Exercise 2.3 In a random sample of 70 automobiles registered in a certain state, 28 of them were found to have emission levels that exceed a state standard. Find a 95% confidence interval for the proportion of automobiles in the state whose emission levels exceed the standard. Answer : [0.2852, ]

Example 2.5: Two separate surveys were carried out to investigate whether or not the users of Plus highway were in favour of raising the speed limit on highways. Of the 250 car drivers interviewed, 220 were in favour of raising the speed limit while of the 200 motorists interviewed, 180 were in favour of raising the speed limit. Find a 95% confidence interval for the difference in proportion between the car drivers and motorist who are in favour of raising the speed limit.

Solution: Hence, 95% CI : We are 95% confident that the difference between the car drivers and motorist who are in favour of raising the speed limits lies between and

Exercise 2.4 In a test of the effect of dampness on electric connections, 100 electric connections were tested under damp conditions and 150 were tested under dry conditions. Twenty of the damp connections failed and only 10 of dry ones failed. Find a 90% confidence interval for the difference between the proportions of connections that fail when damp as opposed to dry. Answer : [0.0591, 0.207]

Error of estimation and choosing the sample size When we estimate a parameter, all we have is the estimate value from n measurements contained in the sample. There are two questions that usually arise: (i) How far our estimate will lie from the true value of the parameter? (ii) How many measurements should be considered in the sample?

The distance between an estimate and the estimated parameter is called the error of estimation. For example if most estimates are within 1.96 standard deviations of the true value of the parameter, then we would expect the error of estimation to be less than 1.96 standard deviations of the estimator, with the probability approximately equal to 0.95.

Example 2.6: The college president asks the statistics teacher to estimate the average age of the students at their college. The statistics teacher would like to be 99% confident that the estimate should be accurate within 1 year. From the previous study, the standard deviation of the ages is known to be 3 years. How large a sample is necessary?

Solution: From the table,

Exercise 2.5: The diameter of a two years old Sentang tree is normally distributed with a Standard deviation of 8 cm. How many trees should be sampled if it is required to estimate the mean diameter within ± 1.5 cm with 95% confidence interval? Answer : 110 trees

EXERCISES

Exercise 2.6 A tire manufacturer wishes to investigate the tread life of its tires. A sample of 10 tires driven 50, 000 miles revealed a sample mean of 0.32 inches of tread remaining with a standard deviation of 0.09 inches. Construct a 95 percent confidence interval for the population mean. Would it be reasonable for the manufacturer to conclude that after 50, 000 miles the population mean amount of tread remaining is 0.30 inches? Answer : [0.2556, ]

Exercise 2.7 Resin-based composites are used in restorative dentistry. A comparison of the surface hardness of specimens cured for 40 seconds with constant power with that of specimens cured for 40 seconds with exponentially increasing power. 15 specimens were cured with each method. Those cured with constant power had an average surface hardness (in N/mm) of with a standard deviation of Those cured with exponentially increasing powder had an average surface hardness of with a standard deviation of 6.1. Find a 98% confidence interval for the difference in mean hardness between specimens cured by two methods. Answer: [ , ]

Exercise: 2.8 The wedding ceremony for a couple, Jamie and Robbin will be held in Menara Kuala Lumpur. A survey has been carried out to determine the proportion of people who will come to the ceremony. From 250 invitations, only 180 people agree to attend the ceremony. Find a 90% confidence interval estimate for the proportion of all people who will attend the ceremony. Answer : [0.6733, ]