Download STP226, Summer 99 Review notes for Test #1

STP420 Spring 2007
Review notes for Test #1.
1. Know new vocabulary and symbolic notation,
for example: frequency, relative frequency, mean, median, quartiles, percentiles, deciles,
mode, range, stem- and leaf plot, box plot, density curve etc. Know what is a symbol for
population mean, standard deviation and sample mean and standard deviation.
Know the types of variables in the data (quantitative, qualitative, etc )
2. Know how to graphically represent your data and how to read and interpret
given graphs and tables.
• Box plot
• Histogram
• Frequency Table
• Stemplot
• Scatterplot
3. Know all measures of center and dispersion for the sample. You need to know how to
compute sample standard deviation by hand from the definition.
Make sure to know how to interpret each measure, what each tells you about the
data. Be able to compare mean and median for symmetric and skewed data. Know how to
use IQR to check for outliers in the data. Know how change in measurements affects
measures of center and dispersion.
4. Know how to describe the shape of the distribution (Symmetric, left skewed,
slightly right skewed etc.) from all types of data displays. Be able to decide whether the
means and standard deviations of two given distribution curves are different or not
(from the graph).
Be able to point out approximate location of median and mean of the given
distribution curve (from the graphical display)
5. Know what is the density curve. Study normal and standard normal curve. Know
68-95-99.7 rule. Know how to find areas under st. normal and normal curve.
Know what is z- score and what you use it for. If variable is normally distributed,
know for example what is the % that exceeds a certain value or what is the value
that marks lower 5 % of your data.
6. Know how to obtain the least squares regression line. You may use a calculator.
Know when regression may be used (scatterplots show linear trend).
Know that least squares regression line minimizes sum of squared errors, where
error=(observed y – predicted y). Compute and interpret r and r2 (r gives strength and
direction of linear relationship of x and y, r2 gives % of total variability in observed y
values that is explained by the regression line. Make sure that you know that correlation
does not necessarily mean causation. Find predictions for given x values. Know warning
about extrapolation.
What is an outlier and influential observation? How to check if observation is influential.
Know about residual plots and how they may indicate problems with the regression.
Know what is the meaning of the slope of the regression line and what are its units. Is r
and r2 changing with units change in your data (lb. to kg for example)?
7.
Know the difference between an observational study and a designed
experiment. What are principals of experimental design? For a given study
identify experimental units, treatment, response.
Know how to select a simple random sample (SRS) from a population by using random
numbers tables.
Know about different types of sampling procedures, know example of each:
SRS, Stratified sample, Multistage sample, Systematic random sample.
What is Voluntary response sample and what is the problem with such a sample?
8. Be aware that what is a statistics, what is a parameter. Know that variability of a
statistics decreases with increasing sample size. Spread of the sampling distribution is
about the same for fixed n, regardless of the population size, as long as population is
much larger than the sample. Know what is a sampling distribution of a statistics. What
makes a statistics an unbiased estimate of a parameter of the population?