6.2 confidence intervals for the mean (small samples) statistics mrs. spitz spring 2009

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6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

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Page 1: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

6.2 Confidence Intervals for the Mean (Small Samples)

StatisticsMrs. SpitzSpring 2009

Page 2: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Objectives/Assignment

How to interpret the t-distribution and use a t-distribution table

How to construct confidence intervals when n < 30 and is unknown

Assignment: pp. 271-273 #1-26

Page 3: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

The t-Distribution

In many real-life situations, the population standard deviation is unknown. Moreover, because of various constraints such as time and cost, it is often not practical to collect samples of size 30 or more. So, how can you construct a confidence interval for a population mean given such circumstances? If the random variable is normally distributed (or approximately normal), the sampling distribution for is a t-distribution.x

Page 4: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009
Page 5: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Definition continued . . .

Page 6: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Note:

Table 5 of Appendix B lists critical values of t for selected confidence intervals and degrees of freedom. Pg. A20

Page 7: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Concept: Degrees of freedom

Suppose there are an equal number of chairs in a classroom as there are students: 25 chairs and 25 students. Each of the first 24 students to enter the classroom has a choice as to which chair he or she will sit in. There is no freedom of choice, however, for the 25th student who enters the room.

Page 8: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Example 1: Finding Critical Values of t

Find the critical value tc, for a 95% confidence when the sample size is 15.

SOLUTION: Because n = 15, the degrees of freedom are:

d.f. = n – 1 = 15 – 1 = 14

A portion of Table 5 is shown. Using d.f. = 14 and c = 0.95, you can find the critical value, tc, as shown by the highlighted areas in the table.

Page 9: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009
Page 10: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

The graph shows the t-distribution for 14 degrees of freedom, c = 0.95 and tc = 2.145

Page 11: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Note:

After 30 d.f., the t-values are close to the z-values. Moreover, the values in the table that show ∞ d.f. correspond EXACTLY to the normal distribution values.

Page 12: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Try it yourself #1:

Find the critical value tc, for a 90% confidence when the sample size is 22.

SOLUTION: Because n = 22, the degrees of freedom are:

d.f. = n – 1 = 22 – 1 = 21

A portion of Table 5 is shown. Using d.f. = 21 and c = 0.90, you can find the critical value, tc, as shown by the highlighted areas in the table.

Page 13: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

A. Identify the degrees of freedom: 21

B. Identify the level of confidence: 0.90

C. Use Table 5 to find t: 1.721

Three things to do:

Page 14: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Study Tip:

Unlike the z-table, critical values for a specific confidence interval can be found in the column headed by c in the

appropriate d.f. row. (The symbol ∝ will be explained in chapter 7.)

Page 15: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Confidence Intervals and t-Distributions

Constructing a confidence interval using the t-distribution is similar to constructing a confidence interval using the normal distribution—both use a point estimate and a maximum error of estimate, E.

x

Page 16: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Another Study Tip

Before using the t-distribution to construct a confidence interval, you should check that n < 30, is unknown, and the population is approximately normal.

Page 17: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009
Page 18: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Ex. 2: Constructing a Confidence Interval

You randomly select 16 restaurants and measure the temperature of the coffee sold at each. The sample mean temperature is 162 〫 F with a standard deviation of 10 〫〫 F. Find the 95% confidence interval for the mean temperature. Assume the temperatures are approximately normally distributed.

Page 19: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

SOLUTION:

Because the sample size is less than 30, is unknown, and the temperatures are approximately normally distributed, you can use the t-distribution. Using n = 16,

is 162, s = 10, c = 0.95 and d.f. =15, you can use Table 5 to find that tc =x

Page 20: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Step 3: Maximum error of Estimate, E.

Step 4: Left/Right endpoints by adding and subtracting from the mean.

Page 21: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Ex. 3: Constructing a Confidence Interval

You randomly select 20 mortgage institutions and determine the current mortgage interest rate at each. The sample mean rate is 6.93% with a sample standard deviation of 0.42%. Find the 99% confidence interval for the mean mortgage rate. Assume the interest rates are approximately normally distributed.

Page 22: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Identify all your necessary info

Sample size is less than 30, is unknown and the interest rates are approximately normally distributed so we can use the t-distribution.

n=20, = 6.93, s = 0.42, c = 0.99, and d.f. = 19.

Find the maximum error of estimate at the 99% confidence interval:

x

Page 23: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Step 3: Maximum Error of Estimate

Step 4: Subtract/Add 0.269 to x

Page 24: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Flowchart will help!

Page 25: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Ex. 4: Choosing the Normal or t-Distribution

You randomly select 25 newly constructed houses. The sample mean construction cost is $181,000 and the population standard deviation is $28,000. Assuming construction costs are normally distributed, should you use the normal distribution, the t-distribution or neither to construct a 95% confidence interval for the mean construction cost? Explain your reasoning.

Page 26: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Ex. 4: Choosing the Normal or t-Distribution

SOLUTION: Because the population is normally distributed and the standard deviation is known, you should use the normal distribution.

Page 27: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Try it yourself #4

You randomly select 18 adult male athletes and measure the resting heart rate of each. The sample mean heart rate is 64 beats per minute. Assuming that the heart rates are normally distributed, should you use the normal distribution, the t-distribution or neither to construct a 90% confidence interval for the mean heart rate? Explain your reasoning.

Page 28: 6.2 Confidence Intervals for the Mean (Small Samples) Statistics Mrs. Spitz Spring 2009

Flowchart will help!

Is n ≥ 30?

NO, IT IS 18.

Is population normally or approximately normally distributed?

Yes, normally distributed.

Is known?

No, sample standard deviation only.