An understanding of statistics extends beyond the ability to crunching numbers or use a program to run statistical analyses. As such, an introductory statistics course can provide so much more than the mere attainment of technical skills. Successful completion of an introductory statistics course can enable students to grow as individuals and professionals so that they can make substantial progress toward becoming critical thinkers and people who are truly educated. The class project is a compilation of all the prior homework assignments, readings, and learning—and demonstrates what and how much you’ve learned in the class.

After successful completion of this course you decide that you can earn some extra money as a statistical consultant. Josh comes to you for help. He really wants to win first prize at his school’s science fair. He’s run an experiment testing the effects of music on the growth of plants. Josh thinks that the plants that were exposed to music will grow at a fast rate than plants without music exposure. He was able to obtain 80 newly sprouted bean plants. These plants were randomly assigned to either a music group or a no music group. After two weeks the height of each plant was measured.

Your objective is to provide Josh with a brief written report determining if there is support for Josh’s hypothesis. You have learned and applied all the skills necessary to complete your first statistical consultation. Your goal, and the purpose of this class project, is to compile all pertinent information into one brief report. To help you compile all the necessary material and to ensure you do not miss a step the class project is broken down into three parts: Set-up, examination of descriptive statistics and an examination of inferential statistics.

Part 1: Set-up:

1. Before you can examine the data Josh provided you need to figure out what type of data Josh has. Understanding a research study’s design and knowing what type of data analysis you need to conduct is the best way to start. If you were a researcher you could determine what type of study (experimental vs. observational), and from there you could select what types of variables you want to measure. As a statistical consultant you don’t have much of a say in the matter. Rather you need to take the data you are given and figure what statistics can be run based on the data you have. In part 1 you need to answer the following questions: a. What is the basic question the researcher wants to address using this set of data?
   b. Label your independent variable and the dependent variable.
   c. What is the level of measurement (nominal, ordinal, interval and ratio)?
   d. Is there reason to believe the population is normally distributed?
   e. What type of study does Josh have?
   Part 2: Descriptive Statistics
2. Your next step is to examine the data. At this point you could skip ahead to part 3 and run inferential statistics; after all quick hypothesis test would give us the answer to Josh’s question. A novice consultant might jump ahead and examine the data using inferential statistics. Not you. You paid attention in class and you know that all inferential tests are based on several assumptions. Before you data examine the data using inferential statistics you want to make sure you’re not violating any assumptions. So you decide to examine the data using descriptive statistics. In part 2 you need to answer the following questions:

1. Are the score normal distributed : i. Construct a histogram or other chart to show the nature or shape of the distribution of the data. 1. Hint: a visual inspection of the histogram can answer this question, in other words is the histogram bell-shaped
   ii. Find the mean and median, and the mode, which are measures of center that describe your data. 1. Hint: if the distribution is symmetric it can be considered normal, see skewness on page 104 to see how to determine if the distribution is skewed
2. Variation : Find the range and standard deviation, which are measures of the variation or the amount that the sample values vary among themselves.
3. Outliers : Identify any sample values that lie very far away from the vast majority of the other sample values. i. Hint: you could do this using a visual inspection of the histogram, or you can use the standard deviation to identify extreme scores.
4. Corrections : Based on your inspection of the outliers are there any errors that should be corrected. How would you correct them? Discuss the implications of this result.

Part 3: Inferential Statistics

3. Assuming that all assumptions have been met it is now time for you to conduct a hypothesis testing to determine if Josh’s hypothesis is correct. a. State the hypotheses

b. Set Criteria

c. Select your test statistics and compute the value

d. Make decision

End the paper with a Statement of Conclusions, including reasons why the results might not be correct, along with a description of ways in which the study could be improved, given sufficient time and money. Throughout this text we have emphasized the interpretation of results. A final conclusion to "reject the null hypothesis" alone by itself without explanation is basically worthless to all of those other people who lacked the vision and wisdom to take a statistics course. Computers and calculators are quite good at yielding results, but such results typically require the careful interpretation that breathes life into an otherwise meaningless result. We should recognize that a result is not automatically valid simply because it was computer-generated. Computers don’t think, and they are quite capable of providing results that are quite ridiculous when considered in the context of the real world. We should always apply the most important and indispensable tool in all of statistics: common sense! So be sure to criticize your own data.

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