WS5-2_PivotTables1.docx
WS5-2_PivotTables.docx
The purpose of this document is to review the sections of the research paper template. The research paper template is in APA7 format. It includes a title page, table of contents, List of tables, list of figures, project background, project analysis, project summary, references, and appendices. The table of contents is not automatically updated, so you will need to manually update the page numbers in the table of contents. The project background section was reviewed in the prior workshop.
The three types of Project Analysis techniques are simple linear regression, t test hypothesis testing, and chi-square hypothesis testing. This formative assessment covers the Project Analysis section in more detail, and specifically the simple linear regression analysis. The project analysis section will contain the three forms of analysis needed for these reports to be complete. Both statistics and graphs are imperative to be complete. Any tables or figures shown will need to have APA covered. Tables require a heading of the format Table #. . Figure require a caption under them of the format Figure *<Number>. <Title>.<br />
A chi-square test in hypothesis analysis is used for research when you have sample data with two categories and counts in a contingency table format (summary table with one category as rows, one category as columns and counts in the matrix of values). The chi-square test statistic is a calculation that Excel can provide. In a test on a sample, a hypothesis statement is made about the whether the two categorical variables are independent or not. The null hypothesis statement is that the two categorical variables are independent and the alternative hypothesis is that the categorical variables are not independent. </p>
<p>An example analysis is shown below. The H0 statement is that the categorical variables of depth and magnitude are independent. The H1 statement is that the categorical variables of depath and magnitude are not independent .<br />
The judgment is based on 2 methods. The critical value method would compare the chi-square statistic of .1202 to boundary values of +6.63 and if the chi-square statistic is greater you reject the H0. The p-value method rejects H0 if the p-value is lower that the level of significance. In this case, .7288 is not lower than .01, so do not reject H0.</p>
<p>ASSESSMENT:<br />
Match the following pieces of information to the correct answers.<br />
2 Methods of judging H0 categorical variables are independent<br />
p-value is lower than the level of significance Critical value or p-value<br />
H0 for the analysis above True</p>
<p>ANSWERS</p>
<p>2 Methods of judging H0 categorical variables are independent<br />
p-value is lower than the level of significance Critical value or p-value<br />
H0 for the analysis above True</p>
<p>Chi-Square TestIs depth of earthquake independent of the magnitude?<br />
Use .01 level of significance and quake raw data in worksheet RawData to summarize into counts.<br />
Magnitude (Richter)0-1010-20Total<br />
Notice that >1 takes into account 2 lines of the pivot.<br />
0-111920<br />
Entering values correctly into table: (10 points)<br />
>1151530<br />
Total262450<br />
DO NOT touch the non-blue areas of the tables.<br />
Magnitude (Richter)0-1010-20Total<br />
0-110.40009.600020<br />
>115.600014.400030<br />
Total262450<br />
Level of Significance0.01<br />
Entering correct alpha value (10 points)<br />
Number of Rows2<br />
Number of Columns2<br />
Degrees of Freedom1<br />
Critical Value6.6349<br />
Chi-Square Test Statistic0.1202<br />
p-Value0.7288<br />
Observed Frequencies<br />
Depth (km)<br />
Do not reject the null hypothesis<br />
Expected Frequencies<br />
Depth (km)<br />
Data<br />
Results</p>
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