{"id":7533,"date":"2022-04-27T18:30:20","date_gmt":"2022-04-27T18:30:20","guid":{"rendered":"http:\/\/euseguros.pt\/?p=7533"},"modified":"2022-04-27T19:16:52","modified_gmt":"2022-04-27T19:16:52","slug":"how-to-build-a-2-way-anova-table","status":"publish","type":"post","link":"https:\/\/euseguros.pt\/en\/how-to-build-a-2-way-anova-table\/","title":{"rendered":"How to build a 2-Way ANOVA Table"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.4.3&#8243;][et_pb_row _builder_version=&#8221;4.4.3&#8243;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.4.3&#8243;][et_pb_text _builder_version=&#8221;4.4.3&#8243;]<\/p>\n<h3><strong>How to build a 2-Way ANOVA Table<br \/> <\/strong><\/h3>\n<p>This guide is to help you nail your exams in statistics, so let&#8217;s dive right in.<\/p>\n<p>You will be given a table like the following picture. Let&#8217;s say each column represents 5 Stores from A-E and Each row represents Morning, Afternoon, and Night. The values refer to the average of people in each store during each period.<\/p>\n<p>[\/et_pb_text][et_pb_image src=&#8221;http:\/\/euseguros.pt\/wp-content\/uploads\/2022\/04\/Initial-Table.jpg&#8221; _builder_version=&#8221;4.4.3&#8243;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.4.3&#8243;]<\/p>\n<h3><strong>Step1: Add the Marginals and find the Averages<br \/> <\/strong><\/h3>\n<p>For each column fdo the average and the same for each row.<\/p>\n<p>The green squarw with the value 83 is the averages. It doesn&#8217;t matter if you do (92+82+76)\/3 or (87+86+77+93+74)\/5. Both will lead to this same value.<\/p>\n<p>[\/et_pb_text][et_pb_image src=&#8221;http:\/\/euseguros.pt\/wp-content\/uploads\/2022\/04\/Marginals.jpg&#8221; _builder_version=&#8221;4.4.3&#8243;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.4.3&#8243;]<\/p>\n<h3><strong>Step2: Find Factor A and Factor B and TSS<br \/> <\/strong><\/h3>\n<p>We now have the Total Avg = 83.47<\/p>\n<p><strong>Factor A<\/strong><\/p>\n<p>Factor A(rows) = number of columns * the squared difference in the Marginal Rows(Top to Bottom)<\/p>\n<p>5 * [(92.2-83.47)^2+(82.4-83.47)^2+(75.8-83.47)^2] = 680.93<\/p>\n<p><strong>Factor B<br \/><\/strong><\/p>\n<p>FactorB(Columns) = number of rows * the squared difference in the Marginal columns(Left to Right))<\/p>\n<p>3 * [(87.33-83.47)^2+(86.33-83.47)^2+(77-83.47)^2+(93-83.47)^2+(73.67-83.47)^2] = 755.4<\/p>\n<p><strong>TSS<\/strong><\/p>\n<p>TSS is found bu doing the following:<\/p>\n<p>find the sum of the square of each entry 102^2+&#8230; all the way to the last one+76^2 and subtract by the total number of entries n = 15 * TotalAvg = 83.47^2<\/p>\n<p>This will give you a total of 1,859.7<\/p>\n<p>[\/et_pb_text][et_pb_image src=&#8221;http:\/\/euseguros.pt\/wp-content\/uploads\/2022\/04\/2-way-anova-table.jpg&#8221; _builder_version=&#8221;4.4.3&#8243;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.4.3&#8243;]<\/p>\n<p>To build your 2-way anova table, you need to memorize: the headers: &lt;Source&gt;, DF(Degrees of Freedom), SS(Sum of Squares), MS(Mean Square), F-Test<\/p>\n<p>Then for the rows you enter Factor A(always rows),Factor B(always columns), Residual or Error(same thing) and Total.<\/p>\n<p><strong>Finding DF&#8217;s (Degrees of Freedom)<\/strong><\/p>\n<p>The next step is to enter the DF.<\/p>\n<p><strong>Factor A:<\/strong> We have 3 rows, so the DF are 3-1 = 2<\/p>\n<p><strong>Factor B:\u00a0<\/strong>We have 5 columns, so the DF are 5-1=4<\/p>\n<p><strong>Residual(Error): <\/strong>Multiply Factor A x Factor B = 8<\/p>\n<p><strong>Total: <\/strong>Sum Factor A + Factor B + Error = 2+4+8=14<\/p>\n<p>Moving on, for the SS, we calculated SS for FactorA = 680.93, for Factor B = 755.40 and we also have the TSS which is 1,859.70, so to find the Residual we do the difference between the total and the rest which gives us the residual of 423.37<\/p>\n<p>For the MS you just divide the SS by the DF. So for Factor A we have 680.93\/2 = 340.47, for Factor B we have 755.40\/4 = 188.85\u00a0 and for the Residual we have 423.37 \/ 8 = 52.92<\/p>\n<p>Finally to find F, you divide 340.47\/52.92 = 6.43 for Factor A and for Factor B you do 188.85\/52.92 = 3.57<\/p>\n<p>[\/et_pb_text][et_pb_image src=&#8221;http:\/\/euseguros.pt\/wp-content\/uploads\/2022\/04\/F528.jpg&#8221; _builder_version=&#8221;4.4.3&#8243;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.4.3&#8243;]<\/p>\n<h3><strong>Step3: Do the Test<br \/> <\/strong><\/h3>\n<p>They will ask something like this: &#8220;<span class=\"fontstyle0\">Use the analysis of variance to test whether there is any difference in the average number of people throughout the day(Factor A)&#8221;<\/span><\/p>\n<p><span class=\"fontstyle0\">They will usually tell you to use a specific significance level. Let&#8217;s say they tell you it is 5%.<\/span><\/p>\n<p><span class=\"fontstyle0\">So what you do is use a Statistical F-Distribution Table at 5%(note that there are F-Tables for 10%, 2.5%, so make sure you are using the right one)<\/span><\/p>\n<p><span class=\"fontstyle0\">And you now have the needed values to find the corresponding entry v1= DF of Factor A = 2, and V2 = Residual = 8. From the table we get the value of 4.459<br \/><\/span><\/p>\n<p><span class=\"fontstyle0\">So the 4.459 is the critical value, the crossing point between the H0: (Null Hypothesis) and H1.<\/span><\/p>\n<p><span class=\"fontstyle0\">And you know compare it to the value from the ANOVA table which is 6.43. <\/span><\/p>\n<p><span class=\"fontstyle0\">Since 6.43 is greater than 4.459, this means that:<\/span><\/p>\n<p><span class=\"fontstyle0\">We reject the H0(null) and conclude that there is a difference in the average number of people throughout the day.<br \/><\/span><\/p>\n<p><span class=\"fontstyle0\">If they asked you to test FActor B at 5% as well, you would check the F-Distribution table at 5%, 4, 8 and would find the value 3.838<\/span><\/p>\n<p><span class=\"fontstyle0\">So here we would not reject the Null Hypothesis because the F-Value from the ANOVA table is 3.57 which is less than the Critical Value found from the Distribution table.<\/span><\/p>\n<p>[\/et_pb_text][et_pb_image src=&#8221;http:\/\/euseguros.pt\/wp-content\/uploads\/2022\/04\/F538.jpg&#8221; _builder_version=&#8221;4.4.3&#8243;][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.4.3&#8243;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.4.3&#8243;][et_pb_signup provider=&#8221;aweber&#8221; aweber_list=&#8221;Subscribers|6133958&#8243; success_action=&#8221;redirect&#8221; success_redirect_url=&#8221;http:\/\/euseguros.pt\/novo-subscritor\/&#8221; title=&#8221;Subscribe to our newsletter&#8221; button_text=&#8221;SUBMIT&#8221; description=&#8221;<\/p>\n<p>Get important specialized information to help your business<\/p>\n<p>&#8221; _builder_version=&#8221;4.4.3&#8243; header_level=&#8221;h1&#8243; header_font=&#8221;||||||||&#8221; header_text_align=&#8221;center&#8221; header_font_size=&#8221;31px&#8221; body_font=&#8221;||||||||&#8221; body_text_align=&#8221;center&#8221; result_message_font=&#8221;||||||||&#8221; background_color=&#8221;#000000&#8243; custom_button=&#8221;on&#8221; button_bg_color=&#8221;#e02b20&#8243; button_font=&#8221;||||||||&#8221; max_width=&#8221;100%&#8221; button_letter_spacing_hover=&#8221;0&#8243; fields_text_shadow_style=&#8221;none&#8221; global_module=&#8221;557&#8243; saved_tabs=&#8221;all&#8221; button_text_size__hover_enabled=&#8221;off&#8221; button_one_text_size__hover_enabled=&#8221;off&#8221; button_two_text_size__hover_enabled=&#8221;off&#8221; button_text_color__hover_enabled=&#8221;off&#8221; button_one_text_color__hover_enabled=&#8221;off&#8221; button_two_text_color__hover_enabled=&#8221;off&#8221; button_border_width__hover_enabled=&#8221;off&#8221; button_one_border_width__hover_enabled=&#8221;off&#8221; button_two_border_width__hover_enabled=&#8221;off&#8221; button_border_color__hover_enabled=&#8221;off&#8221; button_one_border_color__hover_enabled=&#8221;off&#8221; button_two_border_color__hover_enabled=&#8221;off&#8221; button_border_radius__hover_enabled=&#8221;off&#8221; button_one_border_radius__hover_enabled=&#8221;off&#8221; button_two_border_radius__hover_enabled=&#8221;off&#8221; button_letter_spacing__hover_enabled=&#8221;on&#8221; button_letter_spacing__hover=&#8221;0&#8243; button_one_letter_spacing__hover_enabled=&#8221;off&#8221; button_two_letter_spacing__hover_enabled=&#8221;off&#8221; button_bg_color__hover_enabled=&#8221;off&#8221; button_one_bg_color__hover_enabled=&#8221;off&#8221; button_two_bg_color__hover_enabled=&#8221;off&#8221;][\/et_pb_signup][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>","protected":false},"excerpt":{"rendered":"<p>In this article we will build a 2-Way ANOVA Table so it can help you gain a better understanding in your statistics studies.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[105],"tags":[396],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.8 - 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