This question explores the effect of the sample size on the .pdf

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This question explores the effect of the sample size on the sampling distribution of the mean. a) Open Excel. Select Data Analysis, then select "Random Number Generation" from the available options. Use the following values when prompted to enter them: Click OK. Rename the new worksheet to Q4_a There will be 80 rows and 7 columns filled with numbers in a new Sheet on Excel. Consider each row as a random sample drawn uniformly from the numbers 1 to 10. In this case, you have 80 samples of size 7 . In the first empty cell of the following empty column, enter a formula for the mean of the sample in the first row, then drag this formula down to the last row. In this case, you should enter the formula =AVERAGE(A1:G1) into cell H1. Dragging the formula down from cell H1 to H80 to find the remaining sample means..

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Describe the excel equation that you can use to measure the volumes listed in the table below. For example to measure the median value of the cells between C1 and D4 is given by \"=median(Cl:D4)\". If you use a specific range of cells explain how you chose them. If you are inexperience with excel, you may want to learn about the MIN, MAX, AVERAGE, and STDEV excel functions. Make a well formatted table that lists the volumes you measured (do not calculate these values) Solution To select a specific range of cells in excel: Click the first cell in the range, and then drag to the last cell, or hold down SHIFT while you press the arrow keys to extend the selection. You can also select the firstcell in the range, and then press F8 to extend the selection by using the arrow keys. To stop extending the selection, press F8 again. For specific table selection: Take an example of file content: If I wanted to sum the items in row 1, columns 2-4 (i.e. 11 + 12 + 13) If I were doing it by hand, I\'d type:=SUM(B1:D1) Excel equation to get the volume value for the given table: = product(A1:C1) & = product(A2:C2).

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1. MATH 221 Statistics for Decision Making Week 2 iLab Name:_______________________ Statistical Concepts that you will learn after completing this iLab: · Using Excel for Statistics · Graphics · Shapes of Distributions · Descriptive Statistics · Empirical Rule Week 2 iLab Instructions-BEGIN Ø Data have already been formatted and entered into an Excel worksheet. Ø Obtain the data file for this lab from your instructor. Ø The names of each variable from the survey are in the first row of the Worksheet. This row has a background color of gray to identify it as the variable names. All other rows of the Worksheet represent a certain students’ answers to the survey questions. Therefore, the rows are called observations and the columns are called variables. On page 6 of this lab, you will find a code sheet that identifies the correspondence between the variable names and the survey questions. Ø Follow the directions below and then paste the graphs from Excel in the grey areas for question 1 through 3. Type your answers to questions 4 through 11 where noted in the grey areas. When asked for explanations, please give thorough, multi-sentence or paragraph length explanations. Ø PLEASE NOTE that various versions of Excel may have slightly different formula commands. For example, some versions use =STDEV.S while other versions would use =STDEVS (without the dot before the last “S”). Ø The completed iLab Word Document with your responses to the 11 questions will be the ONE and only document submitted to the dropbox. When saving and submitting the document, you are required to use the following format: Last Name_ First Name_Week2iLab. Week 2 iLab Instructions-END Creating Graphs 1. Create a pie chart for the variable Car Color: Select the column with the Car variable, including the title of Car Color. Click on Insert , and then Recommended Charts . It should show a clustered column and click OK . Once the chart is shown, right click on the chart (main area) and select Change Chart Type . Select Pie and OK . Click on the pie slices, right click Add Data Labels , and select Add Data Callouts . Add an appropriate title. Copy and paste the chart here. (4 points) 2. Create a histogram for the variable Height. You need to create a frequency distribution for the data by hand. Use 5 classes, find the class width, and then create the classes. Once you have the classes, count how many data points fall within each class. It may be helpful to sort the data based on the Height variable first. Create a new worksheet in Excel by clicking on the + along the bottom of the screen and type in the categories and the frequency for each category. Then select the frequency table, click on Insert , then Recommended Charts and choose the column chart shown and click OK . Right click on one of the bars and select Format Data Series . In the pop up box, change the Gap Width to 0. Add an appropriate t.

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PAGE 1 Using Microsoft Excel 2010 for Selected Tasks (Throughout this document, a set of data refers to observations of just one variable.) (1) To portray as a bar chart a given frequency, relative frequency, or percentage distribution of a set of qualitative data, one may: With the categories in one column and the counts or proportions or percentages in another: 1. Select (by clicking-and-dragging) the counts or proportions or percentages. 2. Choose (from upper menu) Insert, then Column (for vertical bars) or Bar (for horizontal bars), then the first pictured sub-type. 3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories, click OK, and click OK. 4. Choose (from upper menu) Layout, then Axis Titles to enter appropriate labels for the horizontal and vertical axes, then Chart Title to enter an appropriate title. 5. If you wish the counts or proportions or percentages to be shown on the bars: Choose (from menu) Data Labels, then your preferred position. (2)To portray as a pie chart a given frequency, relative frequency, or percentage distribution, one may: With the categories or numeric classes in one column and the counts or proportions or percentages in another: 1. Select (by clicking-and-dragging) the counts or proportions or percentages. 2. Choose (from upper menu) Insert, then Pie, then the first pictured sub-type. 3. Right-click on a blank spot in the chart area, choose Select Data…, choose (right of center) Edit, enter the location of the categories or numeric classes, click OK, and click OK. 4. (a) Choose (from upper menu) Layout, then Data Labels, then More Data Label Options (which will by default cause each “Value”--i.e, each count or proportion or percentage selected in step 1.--to appear on or near a pie slice); (b) if you wish each category or numeric class to appear on or near a pie slice, select Category name, then your preferred position; (c) click on Close; and (d) if the legend box is now superfluous, delete it. 5. Choose (from menu) Chart Title to enter an appropriate title. (3) Counting the number of cells (within some range of cells) satisfying a particular condition: Examples: · To count how many of the cells A1 through A100 contain the word Agree, one may enter in some blank cell =COUNTIF(A1:A100, “Agree”) Note: In lieu of typing in “Agree”, one may click on a cell containing the word Agree. · To count how many of the cells A1 through A100 contain the number 89, one may enter in some blank cell =COUNTIF(A1:A100, 89) Note: In lieu of typing in 89, one may click on a cell containing the number 89. · To count how many of the cells A1 through A100 contain a number in the interval 10 to under 20, enter in some blank cell =COUNTIF(A1:A100,”<20”)-COUNTIF(A1:A100,”<10”) · Note: Each relative address A1:A100 above may be replaced by the absolute address $A$1:$A$100. In lieu of typing in the absolute address $A$1:$A$100, .

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BUS 308 Week 3 Lecture 3 Setting up ANOVA and Chi Square Expected Outcomes After reading this lecture, the student should know how to: 1. Set-up the data for an ANOVA analysis. 2. Set-up and perform an ANOVA test. 3. Set-up a table of mean differences. 4. Set-up and perform a Chi Square test. Overview Setting up the ANOVA test is quite similar to how the t and F tests were set up. The Chi Square set-up is a bit more complex, as it is not found in the Data Analysis list of tools. ANOVA The set-up of ANOVA within Excel is very similar to how we set up the F and T tests last week; place the data set in appropriate groups and then use the ANOVA input box. One difference this week is that the Fx (or Formulas) list does not include an option for ANOVA, so we need to use the Data | Analysis tools. Data Set-up Single Factor. As with the t-test, ANOVA has a couple of versions to select between. Each is used to answer slightly different questions, and these will be examined below. The most significant difference lies in the data table used for each version. We will be working primarily with the ANOAV Single Factor, which deals with examining possible differences between the means of a single variable within different groups. A question of whether or not the mean compa-ratios are equal across the grades is an example of the kind of question answered with this approach. Question 1. Week 3’s first question is about salary mean equality across the grades. Our lecture example will deal with compa-ratio mean equality across the grades. The set-up for the Single Factor ANOVA we just went through assumed this. The initial steps in the hypothesis testing process are similar to what we have done before: Step 1: Ho: All Compa-Ratio means are equal across the grades Ha: At least one compa-ratio mean differs Notice that these are the standard ANOVA – Single factor null and alternate hypothesis statements that identify the specific variable (compa-ratio) and statistic (mean) that we are testing, and merely say “no difference” and “at least one differs.” Step 2: Alpha = 0.05 Step 3: F statistic and Single Factor ANOVA; used to test multiple means Step 4: Decision Rule: Reject Ho if the p-value < 0.05 Step 5: Conduct the test – place the test function in cell K08. As with the F and T tests, we need to group the data into distinct groups. For example, if we are going to test the compa-ratio mean across grades, then the data must be set-up in a table with grades across the top, as in the screen shot below. Note that as was done with the T and F test input data, the raw or initial data was listed and then sorted. Values were then copied into related groups; we used male and female groups for the F and t tests and grade groups for this test. Test Set-up. Go to the Data | Analysis and select ANOVA Single Factor gives us the following input screen. This is completed for our compa-ratio ...

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