Presentation is loading. Please wait.

Presentation is loading. Please wait.

Chapter 4: Sampling and Statistical Inference

Similar presentations


Presentation on theme: "Chapter 4: Sampling and Statistical Inference"— Presentation transcript:

1 Chapter 4: Sampling and Statistical Inference
Part 2: Estimation

2 Types of Estimates Point estimate – a single number used to estimate a population parameter Interval estimate – a range of values between which a population parameter is believed to be

3 Common Point Estimates

4 Theoretical Issues Unbiased estimator – one for which the expected value equals the population parameter it is intended to estimate The sample variance is an unbiased estimator for the population variance

5 Confidence Intervals Confidence interval (CI) – an interval estimated that specifies the likelihood that the interval contains the true population parameter Level of confidence (1 – a) – the probability that the CI contains the true population parameter, usually expressed as a percentage (90%, 95%, 99% are most common).

6 Confidence Intervals for the Mean - Rationale

7 Confidence Interval for the Mean – s Known
A 100(1 – a)% CI is: x  z/2(/n) z/2 may be found from Table A.1 or using the Excel function NORMSINV(1-a/2)

8 Confidence Interval for the Mean, s Unknown
A 100(1 – a)% CI is: x  t/2,n-1(s/n) t/2,n-1 is the value from a t-distribution with n-1 degrees of freedom, from Table A.3 or the Excel function TINV(a, n-1)

9 Relationship Between Normal Distribution and t-distribution
The t-distribution yields larger confidence intervals for smaller sample sizes.

10 PHStat Tool: Confidence Intervals for the Mean
PHStat menu > Confidence Intervals > Estimate for the mean, sigma known…, or Estimate for the mean, sigma unknown…

11 PHStat Tool: Confidence Intervals for the Mean - Dialog
Enter the confidence level Choose specification of sample statistics Check Finite Population Correction box if appropriate

12 PHStat Tool: Confidence Intervals for the Mean - Results

13 Confidence Intervals for Proportions
Sample proportion: p = x/n x = number in sample having desired characteristic n = sample size The sampling distribution of p has mean p and variance p(1 – p)/n When np and n(1 – p) are at least 5, the sampling distribution of p approach a normal distribution

14 Confidence Intervals for Proportions
A 100(1 – a)% CI is: PHStat tool is available under Confidence Intervals option

15 Confidence Intervals and Sample Size
CI for the mean, s known Sample size needed for half-width of at most E is n  (z/2)2(s2)/E2 CI for a proportion Sample size needed for half-width of at most E is Use p as an estimate of p or 0.5 for the most conservative estimate

16 PHStat Tool: Sample Size Determination
PHStat menu > Sample Size > Determination for the Mean or Determination for the Proportion Enter s, E, and confidence level Check Finite Population Correction box if appropriate

17 Confidence Intervals for Population Total
A 100(1 – a)% CI is: N x  tn-1,a/2 PHStat tool is available under Confidence Intervals option

18 Confidence Intervals for Differences Between Means
Population 1 Population 2 Mean m1 m2 Standard deviation s1 s2 Point estimate x1 x2 Sample size n1 n2 Point estimate for the difference in means, m1 – m2, is given by x1 - x2

19 Independent Samples With Unequal Variances
A 100(1 – a)% CI is: x1 -x2  (ta/2, df*) Fractional values rounded down df* =

20 Independent Samples With Equal Variances
A 100(1 – a)% CI is: x1 -x2  (ta/2, n1 + n2 – 2) where sp is a common “pooled” standard deviation. Must assume the variances of the two populations are equal.

21 Paired Samples A 100(1 – a)% CI is: D  (tn-1,a/2) sD/n
Di = difference for each pair of observations D = average of differences PHStat tool available in the Confidence Intervals menu

22 Differences Between Proportions
A 100(1 – a)% CI is: Applies when nipi and ni(1 – pi) are greater than 5

23 Sampling Distribution of s
The sample standard deviation, s, is a point estimate for the population standard deviation, s The sampling distribution of s has a chi-square (c2) distribution with n-1 df See Table A.4 CHIDIST(x, deg_freedom) returns probability to the right of x CHIINV(probability, deg_freedom) returns the value of x for a specified right-tail probability

24 Confidence Intervals for the Variance
A 100(1 – a)% CI is:

25 PHStat Tool: Confidence Intervals for Variance - Dialog
PHStat menu > Confidence Intervals > Estimate for the Population Variance Enter sample size, standard deviation, and confidence level

26 PHStat Tool: Confidence Intervals for Variance - Results

27 Time Series Data Confidence intervals only make sense for stationary time series data

28 Probability Intervals
A 100(1 – a)% probability interval for a random variable X is an interval [A,B] such that P(A X  B) = 1 – a Do not confuse a confidence interval with a probability interval; confidence intervals are probability intervals for sampling distributions, not for the distribution of the random variable.


Download ppt "Chapter 4: Sampling and Statistical Inference"

Similar presentations


Ads by Google