To Exam Info

Review Guide for Midterm

Bring to Midterm

• One page of crib notes with writing on both sides.

• The Standard Normal table.

You may use the following on the Lab computers:

Excel    SPSS    Windows Calculator

Study

• Course Notes, especially Review Questions at the beginning of each lecture.

• Midterm Practice Questions

• Activities and homeworks.

Exam Format

• Exam questions will be of the following possible formats:
  Definitions; Short Answer; Short Essay; Perform and interpret an SPSS analysis.

• Some questions will be written only. Others will be answered on the computer.

Definitions

1. Categorical (nominal) variable, continuous (scale) variable, univariate dataset, median, Q0, Q1, Q2, Q3, Q4, histogram, bin, boxplot, inner fence, outer fence, mild outlier, extreme outlier, accuracy vs. precision (for an explanation of the difference, see this web site: www.mathsisfun.com/accuracy-precision.html), bias, variance, sample mean (x), sample standard deviation (SD+), SE for the mean (SE_mean = SE_x / √n), normal distribution, inflection point, center (μ), spread (σ), z-score, percentile, correlation, probability, risk (expected value), multiplication rule, meter (old and new definitions), second, kilogram, metric prefixes (pico, nano, micro, milli, centi, kilo, mega, giga, tera).

Written Questions or Problems

1. Discuss the original and current official definitions of the meter, second, and kilogram.

2. Determine Q0, Q1, Q2, Q3, Q4 and IQR for a univariate dataset by hand and by using SPSS.

3. Be able to sort a univariate dataset using SPSS.

4. Compute and chart a histogram by hand or by using SPSS.

5. Determine the outliers for a univariate dataset by using a boxplot or by using z-scores.

6. Compute x and SD+ of a univariate dataset by hand or by using SPSS.

7. Explain what standard deviation is to a person that does not understand statistics. Check out this web reference: www.mathsisfun.com/standard-deviation.html.

8. Compute z-scores with SPSS.

9. Using a standard normal table or SPSS, compute proportions under a normal curve.

10. Using a standard normal table or SPSS, compute percentiles for a normal curve.

11. Compute the correlation of a bivariate dataset using SPSS.

12. Compute the R-squared value of a bivariate dataset using SPSS, and a calculator.

13. Create a scatterplot of a bivariate dataset including a linear trend line using SPSS.