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Assignment checklist

Turn in the following typed (12 point) and stapled packet for your final project:
____ Cover sheet containing your name(s), class time, and the name of your study
____ Summary , which includes all items listed on summary checklist
____ Solution sheet neatly and completely filled out. The solution sheet does not need to be typed.
____ Graphic representation of your data , created following the guidelines previously discussed; include only graphs which are appropriate and useful.
____ Raw data collected AND a table summarizing the sample data ( n , x ¯ and s ; or x , n , and p ’, as appropriate for your hypotheses); the raw data does not need to be typed, but the summary does. Hand in the data as you collected it. (Either attach your tally sheet or an envelope containing your questionnaires.)

Bivariate data, linear regression, and univariate data

Student learning objectives

  • The students will collect a bivariate data sample through the use of appropriate sampling techniques.
  • The student will attempt to fit the data to a linear model.
  • The student will determine the appropriateness of linear fit of the model.
  • The student will analyze and graph univariate data.


  1. As you complete each task below, check it off. Answer all questions in your introduction or summary.
  2. Check your course calendar for intermediate and final due dates.
  3. Graphs may be constructed by hand or by computer, unless your instructor informs you otherwise. All graphs must be neat and accurate.
  4. All other responses must be done on the computer.
  5. Neatness and quality of explanations are used to determine your final grade.

Part i: bivariate data


____State the bivariate data your group is going to study.

Here are two examples, but you may NOT use them: height vs. weight and age vs. running distance.

____Describe your sampling technique in detail. Use cluster, stratified, systematic, or simple random sampling (using a random number generator) sampling. Convenience sampling is NOT acceptable.
____Conduct your survey. Your number of pairs must be at least 30.
____Print out a copy of your data.


____On a separate sheet of paper construct a scatter plot of the data. Label and scale both axes.
____State the least squares line and the correlation coefficient.
____On your scatter plot, in a different color, construct the least squares line.
____Is the correlation coefficient significant? Explain and show how you determined this.
____Interpret the slope of the linear regression line in the context of the data in your project. Relate the explanation to your data, and quantify what the slope tells you.
____Does the regression line seem to fit the data? Why or why not? If the data does not seem to be linear, explain if any other model seems to fit the data better.
____Are there any outliers? If so, what are they? Show your work in how you used the potential outlier formula in the Linear Regression and Correlation chapter (since you have bivariate data) to determine whether or not any pairs might be outliers.

Part ii: univariate data

In this section, you will use the data for ONE variable only. Pick the variable that is more interesting to analyze. For example: if your independent variable is sequential data such as year with 30 years and one piece of data per year, your x -values might be 1971, 1972, 1973, 1974, …, 2000. This would not be interesting to analyze. In that case, choose to use the dependent variable to analyze for this part of the project.
_____Summarize your data in a chart with columns showing data value, frequency, relative frequency, and cumulative relative frequency.
_____Answer the following question, rounded to two decimal places:

  1. Sample mean = ______
  2. Sample standard deviation = ______
  3. First quartile = ______
  4. Third quartile = ______
  5. Median = ______
  6. 70th percentile = ______
  7. Value that is 2 standard deviations above the mean = ______
  8. Value that is 1.5 standard deviations below the mean = ______
_____Construct a histogram displaying your data. Group your data into six to ten intervals of equal width. Pick regularly spaced intervals that make sense in relation to your data. For example, do NOT group data by age as 20-26,27-33,34-40,41-47,48-54,55-61 . . . Instead, maybe use age groups 19.5-24.5, 24.5-29.5, . . . or 19.5-29.5, 29.5-39.5, 39.5-49.5, . . .
_____In complete sentences, describe the shape of your histogram.
_____Are there any potential outliers? Which values are they? Show your work and calculations as to how you used the potential outlier formula in Descriptive Statistics (since you are now using univariate data) to determine which values might be outliers.
_____Construct a box plot of your data.
_____Does the middle 50% of your data appear to be concentrated together or spread out? Explain how you determined this.
_____Looking at both the histogram AND the box plot, discuss the distribution of your data. For example: how does the spread of the middle 50% of your data compare to the spread of the rest of the data represented in the box plot; how does this correspond to your description of the shape of the histogram; how does the graphical display show any outliers you may have found; does the histogram show any gaps in the data that are not visible in the box plot; are there any interesting features of your data that you should point out.

Due dates

  • Part I, Intro: __________ (keep a copy for your records)
  • Part I, Analysis: __________ (keep a copy for your records)
  • Entire Project, typed and stapled: __________

    ____ Cover sheet: names, class time, and name of your study

    ____ Part I: label the sections “Intro” and “Analysis.”

    ____ Part II:

    ____ Summary page containing several paragraphs written in complete sentences describing the experiment, including what you studied and how you collected your data. The summary page should also include answers to ALL the questions asked above.

    ____ All graphs requested in the project

    ____ All calculations requested to support questions in data

    ____ Description: what you learned by doing this project, what challenges you had, how you overcame the challenges


Include answers to ALL questions asked, even if not explicitly repeated in the items above.

Questions & Answers

what do they mean in a question when you are asked to find P40 and P88
Megrina Reply
I dont get your question! What are you talk ING about?
you're asked to find page 40 and page 88 on that particular book.
any suggestions for statistics app better than this
sorry miss wrote the question
No problem) By the way. I NEED a program For statistical data analysis. Any suggestion?
Eviews will help u
arey there any data analyst and working on sas statistical model building
IMAGESNEWSVIDEOS A Dictionary of Computing. measures of location Quantities that represent the average or typical value of a random variable (compare measures of variation). They are either properties of a probability distribution or computed statistics of a sample. Three important measures are the mean, median, and mode.
Ahmed Reply
define the measures of location
Kaynaat Reply
IMAGESNEWSVIDEOS A Dictionary of Computing. measures of location Quantities that represent the average or typical value of a random variable (compare measures of variation). They are either properties of a probability distribution or computed statistics of a sample. Three important measures are th
what is confidence interval estimate and its formula in getting it
Jhezarie Reply
discuss the roles of vital and health statistic in the planning of health service of the community
given that the probability of
can man city win Liverpool ?
Emmanuel Reply
There are two coins on a table. When both are flipped, one coin land on heads eith probability 0.5 while the other lands on head with probability 0.6. A coin is randomly selected from the table and flipped. (a) what is probability it lands on heads? (b) given that it lands on tail, what is the Condi
Nusrat Reply
what is gradient descent?
Saurav Reply
It should be a Machine learning terms。
it is a term used in linear regression
what are the differences between standard deviation and variancs?
what is statistics
Emmanuel Reply
statistics is the collection and interpretation of data
the science of summarization and description of numerical facts
Is the estimation of probability
mr. zaini..can u tell me more clearly how to calculated pair t test
do you have MG Akarwal Statistics' book Zaini?
Haai how r u?
maybe .... mathematics is the science of simplification and statistics is the interpretation of such values and its implications.
can we discuss about pair test
what is outlier?
Usama Reply
outlier is an observation point that is distant from other observations.
what is its effect on mode?
Outlier  have little effect on the mode of a given set of data.
How can you identify a possible outlier(s) in a data set.
The best visualisation method to identify the outlier is box and wisker method or boxplot diagram. The points which are located outside the max edge of wisker(both side) are considered as outlier.
@Daniel Adunkwah - Usually you can identify an outlier visually. They lie outside the observed pattern of the other data points, thus they're called outliers.
what is completeness?
I am new to this. I am trying to learn.
I am also new Dom, welcome!
please my friend i want same general points about statistics. say same thing
outliers do not have effect on mode
also new
I don't get the example
Hadekunle Reply
ways of collecting data at least 10 and explain
Ridwan Reply
Example of discrete variable
Bada Reply
sales made monthly.
I am new here, can I get someone to guide up?
dies outcome is 1, 2, 3, 4, 5, 6 nothing come outside of it. it is an example of discrete variable
continue variable is any value value between 0 to 1 it could be 4digit values eg 0.1, 0.21, 0.13, 0.623, 0.32
How to answer quantitative data
Alhassan Reply
what's up here ... am new here
sorry question a bit unclear...do you mean how do you analyze quantitative data? If yes, it depends on the specific question(s) you set in the beginning as well as on the data you collected. So the method of data analysis will be dependent on the data collecter and questions asked.
how to solve for degree of freedom
Quantitative data is the data in numeric form. For eg: Income of persons asked is 10,000. This data is quantitative data on the other hand data collected for either make or female is qualitative data.
Degree of freedom is the unconditionality. For example if you have total number of observations n, and you have to calculate variance, obviously you will need mean for that. Here mean is a condition, without which you cannot calculate variance. Therefore degree of freedom for variance will be n-1.
data that is best presented in categories like haircolor, food taste (good, bad, fair, terrible) constitutes qualitative data
vegetation types (grasslands, forests etc) qualitative data
I don't understand how you solved it can you teach me
Caleb Reply
solve what?

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Source:  OpenStax, Introductory statistics. OpenStax CNX. May 06, 2016 Download for free at http://legacy.cnx.org/content/col11562/1.18
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