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(10) Sampling & Estimation
Terms in this set (20)
Simple Random Sample
Each item in the population being studied has the same likelihood of being included in the sample
selecting every nth member from a population
Difference between a sample statistic and its corresponding population parameter
Stratified Random Sampling
uses a classification system to separate the population into smaller group based on one or more distinguishing characteristics
Time Series data
Over a period of time at specified equally spaced intervals (Annual Report, Earnings Release)
At a single point in time
Observations over time of the same characteristic for multiple entities
P/E Ratio for companies over the years
Central Limit Theorem
States that for a simple random sample of size n from a population w/ a mean µ and finite variance σ², the sampling distribution of the sample mean approaches a normal probability distribution with mean µ and variance equal to σ²/n
What is the variance of the distribution of the sample mean?
Population variance divided by the sample size σ²/n
Standard Error of the sample mean
Standard deviation of the distribution of the sample means
What happens to the standard error as the population increases?
The standard error decreases
What are the desirable properties of an estimator?
Unbiased: E(x) = µ
Efficient: variance is as small as possible
consistent: Standard Error decreases as sample size increases
Bell shaped and symmetrical about its mean
When would you use a Students-T Distribution?
When the sample size is less than 30 (n<30) and the population variance is unknown but population has a normal, or approximately normal distribution
What are some of the major properties of the t-Distribution?
Single parameter: Degrees of Freedom (df); where df are equal to n-1
More probability in the tails than a normal distribution
For hypothesis testing, which distribution makes it more difficult to reject the null?
What is the level of significance?
What is the CI formula for a population mean when the population has a normal distribution and known variance?
X= Point estimate of population mean
Std Dev/Sqrt(n)= Standard Error
If the population is normal w/ unknown variance, which distribution do you use to construct a CI?
Use the t-distribution
If the distribution is non-normal and n>30, which distribution do you use when:
Population Variance is known
Population Variance is Unknown
Population Variance is known: Z-statistic
Population Variance is Unknown: t-statistic
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