This Minitab Lab Workbook is designed to be used by students taking a one or two semester introductory statistics course. Students should have access to either the professional or student versions of Minitab. Moore and George P. We abbreviate the textbook. We must redo the chapter 13 test and look for the p value. Those using Quick's worksheets should load Mini Others will need to load their page 68 worksheet.
Skip to main content Hello, Sign in. Try Prime Cart. About This Book Elementary Statistics, Ninth Edition, is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. About This Book. Elementary Statistics raises the bar with every edition by incorporating an unprecedented amount of real and interesting data that will help instructors connect with students today, and help them connect statistics to their daily lives.
Minitab Manual. Details about Minitab Manual for Elementary Statistics: The Minitaby Manual is organized to follow the sequence of topics in the text; it contains an easy-to-follow, step-by-step guide on how to use Minitab to perform statistical processes.
This manual is now available on the CD accompanying the text. Hundreds of textbooks reference Minitab products, so our software is easy to add to your course. Find a textbook. The definition of what is meant by statistics and statistical analysis has changed considerably over the last few decades. Wakefield, Dorothy B.
Statistics instructors have been choosing Minitab for more than 40 years because of its user-friendly interface, affordable price, and free online teaching resources. Minitab is the leading software used for statistics education at more than 4, colleges and universities worldwide. Statistics opens a window to the modern world, and this market-leading text makes it easy to understand. The authors carefully Reviews:. In the File command there are two options for saving a Minitab le: 1.
Save Current Worksheet saves only the data. There are options to Save as Type which allows you to save the data as a Minitab worksheet or as an Excel worksheet. Save Project - this option saves the whole Minitab le exactly as it is, including all the output in the session. Last edited by Kazijora.
Want to Read. Share this book. A project can have multiple worksheets associated with it. Also, a project can have associated with it various graphs and records of the commands you have typed and the output obtained while working on the work- sheets. Projects, which are discussed in Appendix A, can be saved and retrieved for later work.
Before we do, however, it is useful to know something about the basic structure of all Minitab commands. The lists that appear may depend on which window is active, e.
If a command name in a list is faded, then it is not available. Typically, using a command from the menu bar requires the use of a dialog box or dialog window that opens when you click on a command in the list. These are used to provide the arguments and subcommands to the command and specify where the output is to go. Double clicking on items in the variable list places them in the box, or, alternatively, you can type them in directly.
Any output is also printed in the Session window. Dialog boxes have a Help button that can be used to learn how to make the entries. For example, suppose that we want to calculate the mean of column C2 in the worksheet marks.
Alternatively, we could have simply typed this entry into the box. Quite often, it is faster and more convenient to simply type your commands directly into the Session window. Sometimes, it is necessary to use the Session window approach, but for many commands the menu bar is available.
So we now describe the use of commands in the Session window. The basic structure of such a command with n arguments is command name E1 ,E2 , Alternatively, we can write command name E1 E Conveniently, if the arguments E1 ,E2 , The command is executed when you hit Enter after an argument name without a continuation character following it. Many commands can, in addition, be supplied with various subcommands that alter the behavior of the command.
En2 ;.. Notice that when there are subcommands each line ends with a semicolon until the last subcommand, which ends with a period. Also, subcommands may have arguments. There are two additional ways in which you can input commands to Minitab.
Also, many commands are available on a toolbar that lies just below the menu bar at the top of the Minitab window. We give a brief discussion of some of the features available in the toolbar in later sections. The simplest approach is to use the Data window to enter data directly into the worksheet by clicking your mouse in a cell and then typing the corresponding data entry and hitting Enter. Remember that you can make a Data window active by clicking anywhere in the window or by using Windows in the menu bar.
You do not need to append the T when referring to the column. Clicking on it alternates between row-wise and column- wise data entry. Certainly, this is an easy way to enter data when it is suitable. Remember, columns are variables and rows are observations! Also, you can have multiple data windows open and move data between them. Use the command File I New to open a new worksheet. These entries are separated by blanks. Alternatively, we could have just left this entry blank.
A missing text value is simply denoted by a blank. Special attention should be paid to missing values. In general, Minitab statistical analyses ignore any cases that contain missing data except that the output of the command will tell you how many cases were ignored because of missing data. It is important to pay attention to this information. If your data is riddled with a large number of missing values, your analysis may be based on very few observations — even if you have a large data set!
Note that if your data is in. This brings up the dialog box shown in Display I. The format statement says that we are going to read in the data accord- ing to the following rule: a numeric variable occupying 5 spaces and with no decimals, followed by a space, a numeric variable occupying 2 spaces with no decimals, a space, a numeric variable occupying 2 spaces with no decimals, a space, a numeric variable occupying 2 spaces with no decimals, a space, and a text variable occupying 1 space.
This rule must be rigorously adhered to or errors will occur. So the rules you need to remember if you use formatted input are that ak indicates a text variable occupying k spaces, kx indicates k spaces, and fk. There are many other features to formatted input that we will not discuss here. Use the Help button in the dialog box for information on these features. Typically, we try to avoid the use of formatted input because it is somewhat cumbersome, but sometimes we must use it.
In the session environment, the read command is available for inputting data into a worksheet with capabilities similar to what we have described. To indicate that there is no more data, we type end and hit Enter. We refer the reader to help for more description of how this command works.
By this we mean that the values of a variable follow some determined rule. There is some shorthand associated with patterned data that can be very convenient. The set command is available in the session window to input patterned data.
For example, suppose we want C6 to contain the 10 entries 1, 2, 3, 4, 5, 5, 4, 3, 2, 1. Also, we can add elements in parentheses. The multiplicative factors k and l can also be used in such a context.
Obviously, there is a great deal of scope for entering patterned data with set. The general syntax of the set command is set E1 where E1 is a column. Typically, this means printing out the worksheet and checking the entries.
For example, with the worksheet marks the dialog box pictured in Display I. The general syntax for the print command is print E Em where E1 , These could serve as weights to calculate a weighted average of the marks in the marks worksheet.
Clicking on OK then makes the assignment. We will talk about further features of Calculator later in this manual. Similarly, we assign values to k2 and k3. The let command is available in the Session window and is quite convenient. The following commands make this assignment and then we check, using the print command, that we have entered the constants correctly.
Note the use of double quotes. This is especially true when there are many variables and constants, as it would be easy to slip and use the wrong column in an analysis and then wind up making a mistake. To assign a name to a variable simply go to the blank cell at the top of the column in the worksheet corresponding to the variable and type in an appropriate name.
For example, we have used studid, statistics, calculus, physics, and gender for the names of C1, C2, C3, C4, and C5, respectively, and these names appear in Display I.
When using the variables as arguments just enclose the names in single quotes. Recall that Minitab is not case sensitive, so it does not matter if we use lower or upper case letters when specifying the names.
For example, we get the following results based on what we have entered into the marks worksheet so far. So far, the only way we could change any entries in the worksheet or add some rows is to reenter the whole worksheet! Editing the worksheet is straightforward because we simply change any cells by retyping their entries and hitting the Enter key.
We can add rows and columns at the end of the worksheet by simply typing new data entries in the relevant cells. To insert a row before a particular row, simply click on any entry in that row and then the menu command Editor I Insert Rows. Fill in the blank entries in the new column.
If you wish to clear a number of cells in a block, click in the cell at the start of the block, and holding the mouse key down, drag the cursor through the block so that it is highlighted in black. Click on the Cut Cells icon on the Minitab taskbar , and all the entries will be deleted. We discuss how to save the contents of a worksheet in I. If you not only want to copy a block of cells to your clipboard but remove them from the worksheet, use the command Edit I Cut Cells or the Cut Cells icon on the Minitab taskbar instead.
A dialog box appears as in Display I. The dialog box shown in Display I. Minitab for Data Management 25 Display I. If you delete an entire row, this is not a problem because the rows below just shift up.
For example, if we delete the third row then in the new worksheet, after the deletion, the third row is now occupied by what was formerly the fourth row. Therefore, you should be very careful, when you are not deleting whole rows, to ensure that you get the result you intended. Note that if you should delete all the entries from a column, this variable is still in the worksheet, but it is empty now. This is a good idea if you have a lot of variables and no longer need some of them.
There are various commands in the Session window available for carrying out these editing operations. For example, the restart command in the Session window can be used to remove all entries from a worksheet. The let command allows you to replace individual entries. The copy command can be used to copy a block of cell from one place to another. The insert command allows you to insert rows or observations anywhere in the worksheet. The delete command allows you to delete rows. The erase command is avail- able for the deletion of columns or variables from the worksheet.
As it is more convenient to edit a worksheet by directly working on the worksheet and using the menu commands, we do not discuss these commands further here. If you exit Minitab before you save your work, you will have to reenter everything. So we recommend that you always save. To use the commands of this section make sure that the Worksheet window of the worksheet in question is active.
The next button takes you to the Desktop and the third button allows you to create a subfolder within the current folder. There are several possibilities including saving the worksheet in other formats, such as Excel. Currently, there is only one.
To print a worksheet, use the command File I Print Worksheet. This will not be the case if we save the worksheet as an. For example, if we want to save the contents of the marks worksheet, this command results in the dialog box of Display I. Here, we have typed in the name marks. Note that while we have chosen a. In the Session window, the commands save and retrieve are available for saving and retrieving a worksheet in the. We refer the reader to help for a description of how these commands work.
Note that after executing a menu command the relevant Session window commands are automatically typed in the Session window. We refer the reader to help for a description of how this command works. This may involve applying some simple transformation to a variable to create a new variable — e. In this section, we present some of the ways of doing this.
Also, make sure that the columns on which you are going to perform these operations correspond to numeric variables! These kinds of operations can also be carried out directly in the Session window using the let command, and in some ways this is a simpler approach.
We can also use these arithmetical operations on the constants K1, K2, etc. For example, suppose that we want to compute the weighted average of the Statistics, Calculus, and Physics grades where Statistics gets twice the weight of the other grades.
For example, suppose we want to compute the natural logarithm of the Statistics mark for each stu- dent. A complete list of such functions is given in the Functions window when All functions is in the window directly above the list. The same result can be obtained using the session command let and the natural logarithm function loge.
There are a number of such functions and a complete list is provided in Appendix B. These functions can be applied to numbers as well as constants. If you want to know the sine of the number 3. For example, suppose that we want the mean of all the Statistics marks, i.
Clicking OK causes the mean of column C2 to be printed in the Session window. If we want to, we can store this result in a constant or column by making an appropriate entry in the Store result in box. We can also compute statistics row-wise.
For example, suppose we want to compute the average of the Statistics, Calculus, and Physics marks. Minitab for Data Management 33 It is also possible to compute column statistics using session commands. The general syntax for column statistic commands is column statistic name E1 where the operation is carried out on the entries in column E1 , and output is written to the screen unless it is assigned to a constant using the let command.
See Appendix B. Also, for most column statistics there are versions that compute row statis- tics, and these are obtained by placing r in front of the column statistic name.
The general syntax for row statistic commands is row statistic name E1. The comparison and logical operators are useful when we have simple ques- tions about the worksheet that would be tedious to answer by inspection. For ex- ample, suppose that we want to count the number of times the Statistics grade was greater than the corresponding Calculus grade in the marks worksheet.
In this case, C6 contains the entries: 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, which the worksheet in Display I. These operations can also be simply carried out using session commands. The logical operators combine with the comparison operators to allow more complicated questions to be asked. For example, suppose we wanted to calculate the number of students whose Statistics mark was greater than their Calculus mark and less than or equal to their Physics mark. Note that the observation with the missing Physics mark is excluded.
We will make reference to these commands at appropriate places throughout the manual. It is probably best to wait to read these descriptions until such a context arises. You can recode numeric into numeric, numeric into text, text into numeric, or text into text by choosing an appropriate subcommand.
For example, suppose in the marks worksheet we want to recode the grades in C2, C3, and C4 so that any mark in the range 0—39 becomes an F, every mark in the range 40—49 becomes an E, every mark in the range 50—59 becomes a D, every mark in the range 60—69 becomes a C, every mark in the range 70—79 becomes a B, every mark in the range 80— becomes an A, and the results are placed in columns C6, C7, and C8, respectively.
Note that this menu command restricts the number of new code values to 8. The session command code allows up to 50 new codes. For example, suppose in the marks worksheet we want to recode the grades in C2, C3, and C4 so that any mark in the range 0—9 becomes a 0, every mark in the range 10—19 becomes 10, etc. The general syntax for the code command is code V1 to code Vn to coden for E E2m where Vi denotes a set of possible values and ranges for the values in columns E E2m , i. Minitab for Data Management 37 Display I.
In the session environment, the concatenate command is available for this operation. The general syntax of the concatenate command is concatenate E For example, in the worksheet marks suppose we want to change the gender variable from text, with male and female denoted by m and f, respectively, to a numerical variable with male denoted by 0 and female by 1.
The conversion table comprises two columns in the worksheet, where one column is text and contains the text values used in the text column, and the second column is numeric and contains the numerical values that you want these changed into. For example, suppose we have entered columns C6 and C7 in the marks worksheet, as shown in Display I. The general syntax for the corresponding session command convert is convert E1 E2 E3 E4 where E1 , E2 are the columns containing the conversion table, E3 is the column to be converted and E4 is the column containing the converted column.
This information can be obtained in the History folder of the Project Manager window. The commands can be copied from wherever they are listed and pasted into the Session window to be reexecuted, so that a number of commands can be executed at once without retyping. These commands can be edited before being executed again.
This is very helpful when you have implemented a long sequence of commands and realize that you made an error early on. Note that even if you use the menu commands, a record is kept only of the corresponding session commands. If values are the same, i. To calculate the ranks of the entries in a column we use the Manip I Rank command. In this case, the ranks are 6.
Note that ordering here could refer to numerical order or alphabetical order, so we also consider ordering text columns. Also, we may want to sort all the rows contained in some subset of the columns in the worksheet by a particular column. The Manip I Sort command allows us to carry out these tasks. For example, replacing C2 by C5 in this box would result in the values in C6 becoming 77, 71, 87, 81, 74, 81, 75, 63, 23, Minitab for Data Management 41 The general syntax of the corresponding session command sort is sort E1 E2.
E2m where E1 is the column to be sorted, and E2 , Note that this sort can also be accomplished using the by subcommand, where the general syntax is sort E1 E2. The descending subcommand can also be used to indicate which sorting variables we want to use in descending order rather than ascending order. In C7 we have stored an index which indicates that column each value in C6 came from with a 1 every time a value came from C2, a 2 every time a value came from C3, and a 3 every time a value came from C4.
It is not necessary to create such an index. In the Session window, this same result can be obtained using the stack command. The general syntax for the stack command is given by stack E1 E2. To unstack values in a column by the values in an index column we use the Manip I Unstack command.
The three columns are C8, C9, and C Note that they are identical to columns C2, C3, and C4, respectively. We must always specify a column containing the subscripts when unstacking a column. The general syntax for the corresponding session command unstack is unstack E1 into E2.
Note that it is also possible to simultaneously unstack blocks of columns. We refer the reader to help or Help for information on this. The following data give the Hi and Low trading prices in Canadian dollars for various stocks on a given day on the Toronto Stock Exchange. Create a worksheet, giving the columns the same variable names, using any of the methods discussed in I. Be careful to ensure that the value of the variable stock starts with a letter.
Print the worksheet to check that you have successfully entered it. Save the worksheet giving it the name stocks. Change the Low value in the stock MGI to 3. Calculate the average of the Hi and Low prices for all the stocks, and save this in a column called average. Calculate the average of all the Hi prices, and save this in a constant called avhi. Similarly, do this for all the Low prices, and save this in a constant called avlo. Save the worksheet using the same name.
Using the Minitab com- mands discussed in I. Save the worksheet. Calculate the ranks of the individual stocks based on their Hi price, and save the ranking in a new column. Using parsums see Appendix B. Multiply C3 times. Find the largest value in C1 such that the corresponding entry in C3 is less than or equal to. By presenting data, we mean convenient and informative methods of conveying the information contained in a data set. There are two basic methods for presenting data, namely graphically and through tabulations.
Still, it can be hard to summarize exactly what these presentations are saying about the data. So the chapter also introduces various summary statistics that are commonly used to convey meaningful information in a concise way. All of these topics can involve much tedious, error prone calculation, if we were to insist on doing them by hand.
Not only are there many far more important things for you to be thinking about, as the text discusses, but you are also likely to make an error.
On the other hand, never blindly trust the computer! Check your results and make sure that they make sense in light of the application. For this, a few simple hand calculations can prove valuable. These relative frequencies then serve as a convenient summarization of the data. If the variable is quantitative, we typically group the data in some way, i. Grouping is accomplished using the Manip I Code command discussed in I.
Quantitative variables are always ordered but sometimes categorical variables are as well, e. Often, it is convenient with quantitative variables to record the empirical distribution function, which for data values x1 ,. We introduce some new commands to carry out the necessary computations using the data shown in Table 1. This is data collected by A. Michelson and Simon Newcomb in concerning the speed of light. Looking At Data—Distributions 49 28 22 36 26 28 28 26 24 32 30 27 24 33 21 36 32 31 25 24 25 28 36 27 32 34 30 25 26 26 25 23 21 30 33 29 27 29 28 22 26 27 16 31 29 36 32 28 40 19 37 23 32 29 -2 24 25 27 24 16 29 20 28 27 39 23 Table 1.
Next we want to record the frequencies, relative frequencies, cumulative frequencies, and cumulative distribution of this grouped variable.
The dialog box for doing this is shown in Display 1. Display 1. The general syntax of the corresponding session command tally is tally E1. If no subcommands are given, then only frequencies are computed, while the subcommands percents computes relative frequencies, cumcnts computes the cumulative frequency function, and cumpcts computes the cumulative distribution of C2.
Any of the subcommands can be dropped. The cumulative distribution is computed for the values in C3 with the unique values in C3 stored in C4 and the cumulative distribution at each of the unique values stored in C5 via the store subcommand to tally. These values are in a sense a summarization of the empirical distribution of the variable. For example, in the newcomb worksheet the dialog box shown in Display 1.
For example, we might want such a summary for each of the groups we created in II. Note that a number of summary statistics can also be computed using the Column Statistics discussed in I. The result of these choices is that the next available variables in the worksheet contain these values. So in this case, the values of C3—C7 are as depicted in Display 1.
Note that these variables are now named as well. Note that many more statistics are available using this command. A by subcommand can also be used. The stats command is available in the Session window if we want to store the values of statistics. We refer the reader to help for a description of this command.
In this section we describe how to use the plotting features in Minitab. There are, however, many features of plotting that we will not describe. For example, there are many graphical editing capabilities that allow you to add features, such as titles or legends. Some of these features are accessed via Graph I Layout. You make any particular Graph window active by clicking in it or by using the Window command. Actually, the data is grouped before plotting and multiple observations in a group are stacked over the x-axis.
For example, for the newcomb worksheet dialog box in Display 1. The general syntax of the corresponding Session command dotplot is dotplot E1. There are a number of subcommands available. The same subcommand ensures the scales of the dotplots are the same for each column.
The by subcommand allows plotting of a variable by the values of another variable with all plots having the same scale. The row containing the median is enclosed in parentheses , and the depth is only the observations on that line.
The second column gives the stems, as determined by Minitab, and the remaining columns give the ordered leaves, where each digit represents one observation. The Leaf Unit determines where the decimal place goes after each leaf. Multiple stem-and-leaf plots can be carried out for a number of columns simultaneously and also for a single variable by the values of another variable.
The Graph I Histogram command is used to obtain these plots. We can produce multiple histograms by placing more variables in the x boxes. As can be seen from the dialog box of Display 1. Looking At Data—Distributions 57 Display 1. An important consideration when plotting multiple histograms is to ensure that all the histograms have the same x and y scales so that the plots are visually comparable. This can be accomplished from the dialog box shown in Display 1.
This has the general syntax histogram E1. There are also subcommands midpoints, nintervals, which spec- ify the number of subintervals, and frequency or percent, which respectively ensure that the heights of the bar lines equal the frequency and relative fre- quency of the data values in the interval. Also, the cumulative subcommand is available so that the bars represent all the values less than or equal to the end- point of an interval. The subcommand same ensures that multiple histograms all have the same scale.
For example, in the newcomb worksheet this command produces the dialog box shown in Display 1. The vertical lines from the hinges are called whiskers, and these run from the hinges to the adjacent values. The adjacent values are given by the greatest value less than or equal to the upper limit the third quartile plus 1. The upper and lower limits are also referred to as the inner fences. As with the plotting of histograms, multiple boxplots can be plotted for comparison purposes, and again, it is important to make sure that they all have the same scale.
There is a corresponding session command called boxplot. We refer the reader to help for more discussion of this command. Looking At Data—Distributions 59 1. In such a context, it is instructive to plot the values of quantitative variables against time in a time series plot. For example, if we had left out connect, only the points would have been plotted. The lines help to visualize the form of the graph. The symbol plotted is a solid circle but other choices could have been made using the Edit Attributes button.
If these observations were made at periodic time intervals, there are other possible choices that could be more meaningful. There is also a corresponding session command tsplot.
We refer the reader to help for more discussion of this. Each distinct value of C1 is plotted along the x-axis simply as a categorical value, not as a quantitative value, and a bar of height equal to the number of times that value occurs in the variable is drawn. A bar chart is a good way to plot categorical variables. There are many possibilities for the types of bar charts drawn, and we refer the reader to the Help button for a discussion of these.
The corresponding session command is chart E1 which produces a bar chart for the values in column E1. Pie charts are a common method for plotting categorical variables. As noted in IPS, this is a value between 0 and 1. These arithmetical operations can be carried out using the let command as described in I. Sometimes, we will want to evaluate the density curve at every value in a column of values, e.
For this we simply click on the radio button Input column and type the relevant column in the associated box. If we plot C2 against C1, we will have a plot of the density curve of this distribution. For this, we use the scatterplot facilities in Minitab as discussed in II. Note that with the normal subcommand we must also specify the mean and the standard deviation via mu and sigma. Again, we can evaluate this function at a single point or at every value in a variable.
The general syntax of the corresponding Session command cdf command with the normal subcommand is cdf E1. Making this change in the dialog box of Display 1. This indicates that the area to the left of The general syntax of the corresponding session command invcdf with the normal subcommand is invcdf E1. A normal probability plot is a diagnostic that checks for the reasonableness of this assumption.
To create such a plot, we use the Graph I Probability Plot command. The normal probability plot is given by the dark dotted curve. The plot also contains other information and further output is printed in the Session window. Of course, the plot should be like a straight line and it is not in this case.
The plot command will be discussed much more extensively in II. The nscores normal scores command relies on some concepts that are beyond the level of this course so we do not discuss this further.
All computations in these exercises are to be carried out using Minitab, and the exercises are designed to ensure that you have a reasonable understanding of the Minitab material in this chapter.
Generally, you should be using Minitab to do all the computations and plotting required for the problems in IPS. Calculate the frequency distribution, the relative frequency distribution, and the cumulative distribution of this ordered categorical variable. Also, use the empirical distribution function to compute the 10th and 90th percentiles. Use Minitab to produce the stemplot of Example 1. Use Minitab to produce the time plot of Example 1.
Looking At Data—Distributions 65 5. Use Minitab commands to compute a numerical summary of this data, and justify your choices. Calculate the means and standard deviations, using any Minitab commands, of both the original and transformed data.
Compute the ratio of the standard deviation of the transformed data to the standard deviation of the original data. Comment on this value.
Justify the outcome. For the N 6, 1. Use Minitab commands to verify the Comment on the shape of this curve.
Use Minitab commands to make the normal quantile plots presented in Figures 1. This chapter considers rela- tionships between two quantitative variables with the remaining cases discussed in later chapters. Graphical methods are very useful in looking for relationships among variables, and we examine various plots for this. By a scatterplot we mean a plot of one variable on the y-axis against the other variable on the x-axis. For exam- ple, consider Example 2. Suppose that we have input the data so that length of the femur measurements are in C1, which has been named femur, and the length of the humerus measurements are in C2, which has been named humerus, of the work- sheet archaeopteryx.
This produces the plot shown in Display 2. Note that we could alter the plotting symbol using the dialog box that appears when we click on the Edit Attributes box. Using the dialog box that appears when you click on the Frame button, you can change the labels on the axes. Also, you can employ the scatterplot smoother lowess to plot a piecewise linear continuous curve through the scatter of points.
Display 2. Looking At Data—Relationships 69 It is also possible to have multiple scatterplots on the same plot. For exam- ple, suppose that C3 in the archaeopteryx worksheet contains the natural log of the femur variable. We obtained the plot of Display 2. The technique of brushing is available after obtaining the plot to see which observations rows the points correspond to. This is helpful in identifying the points that correspond to outliers. Brushing is accessed from the toolbar just below the menu bar by clicking on the brush when the Graph window is active.
The corresponding session command is plot. There are a number of additional plots available in Minitab that are related to the scatterplot. For example, a marginal plot of two variables is a scatterplot of one variable against the other where in addition histograms, dotplots or boxplots are plotted along the sides of the scatterplot for each variable.
These are available via the menu command Graph I Marginal Plot. Matrix plots provide a mechanism for placing a number of scatterplots in a rectangular array or matrix so that they can be directly compared or examined for relationships. For now, we ignore the number recorded as P-Value. The general syntax of the corresponding session command correlate is given by correlate E1.
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