Choose the correct answers for the items listed below.Response = [ Select ] ["Survival Times", "Medications", "Poisons"] Row factor, number of levels = [ Select ] ["Poisons, 4", "Survival Times, 12", "Medications, 3", "Survival Times, 48", "Poisons, 3", "Medications, 4"] Column factor, number of levels = [ Select ] ["Medications, 3", "Poisons, 4", "Medications, 4", "Poisons, 3", "Survival Times, 12", "Survival Times, 48"] Number of treatments = number of samples = [ Select ] ["3", "4", "12", "48", "16"] Number of subjects per sample = [ Select ] ["48", "3", "16", "12", "4"] Total number of observations = [ Select ] ["16", "12", "4", "48", "3"] Variance of the survival times for all animals given Medication D = [ Select ] ["0.01046288", "0.02789318", "0.04386", "0.00387833", "0.10293333", "0.04815379", "0.08373292"] Total survival time for all animals given Poison III = [ Select ] ["4.42", "6.41", "8.12", "4.71", "8.71", "3.77", "9.88"] Average survival time for animals given Poison II and Medication C = [ Select ] ["0.3925", "0.4125", "0.544375", "0.375"] Data from "Statistics For Experimenters" by Box Hunter Hunter, 1978.The data “... appear in a paper by Box and Cox (1964). These are survivaltimes of groups of four animals randomly allocated to three poisons and fourtreatments. The experiment was part of an investigation to combat theeffects of certain toxic agents. This arrangement is called a 3 x 4 factorialdesign and is replicated four times."The aim here is to see how the different poisons and medications affectsurvival times. Survival time is measured in ten-hours.Use the information provided below to answer the SURVIVAL TIMESquestions that follow.Two-way Anova: SURVIVAL TIMES (DATA)MEDICATIONSDMeans0.310.820.430.450.451.10.450.710.61750.460.880.630.660.430.720.760.620.360.920.440.560.290.610.351.02II0.54440.40.490.310.710.231.240.40.380.220.30.230.30.210.370.250.36II0.27630.180.380.240.310.230.290.220.33Means0.31420.67670.39250.53420.4794SNOSIOD Two-way Anova: SURVIVAL TIMES (EXCEL OUTPUT)Anova: Two-FactorSUMMARYABTotalCount444416Sum1.653.522.272.449.88Average0.41250.880.56750.610.6175Variance0.0048250.02586667 0.024558330.012733330.04386Count444416Sum1.283.261.52.678.71Average0.320.8150.3750.66750.544375Variance0.005666670.11310.003233330.0734250.08373292Count44416Sum0.841.340.941.34.42Average0.210.3350.2350.3250.27625Variance0.00046667 0.00216667 0.000166670.00070.00387833TotalCount12121212Sum3.778.124.716.41Average0.31416667 0.676666670.39250.53416667Variance0.01046288 0.10293333 0.027893180.04815379ANOVASource of VariationSdfMSFP-valueF critSample1.03301250.51650625223.22173663.3314E-073.259446306Columns0.9212062530.3070687513.80558243.7773E-062.866265557Interaction0.25013750.041689581.874332640.112250612.363750958Within0.800725360.02224236Total3.0050812547

Two - way ANOVA : The two-way ANOVA is an extension of the one-way ANOVA. The "two-way" comes because each item is classified in two ways, as opposed to one way. For example, one way classifications might be: gender, political party, religion, or race. Two way classifications might be by gender and political party, gender and race, or religion and race. Each classification variable is a called a factor and so there are two factors, each having several levels within that factor. The factors are called the "row factor" and the "column factor" because the data is usually arranged into table format. Each combination of a row level and a column level is called a treatment. From the provided Two - way ANOVA : Response = Survival Times Row factor, number of levels =Poisons, 3 Column factor, number of levels = Medications, 4 Number of treatments = number of samples = 12 Number of subjects per sample =4 Total number of observations =48 Variance of the survival times for all animals given Medication D = 0.04815379 Total survival time for all animals given Poison III =4.42 Average survival time for animals given Poison II and Medication C =0.375

Math

Statistics

Choose the correct answers for the items listed below. Response = [ Select ] ["Survival Times", "Medications", "Poisons"] Row factor, number of levels = [ Select ] ["Poisons, 4", "Survival Times, 12", "Medications, 3", "Survival Times, 48", "Poisons, 3", "Medications, 4"] Column factor, number of levels = [ Select ] ["Medications, 3", "Poisons, 4", "Medications, 4", "Poisons, 3", "Survival Times, 12", "Survival Times, 48"] Number of treatments = number of samples = [ Select ] ["3", "4", "12", "48", "16"] Number of subjects per sample = [ Select ] ["48", "3", "16", "12", "4"] Total number of observations = [ Select ] ["16", "12", "4", "48", "3"] Variance of the survival times for all animals given Medication D = [ Select ] ["0.01046288", "0.02789318", "0.04386", "0.00387833", "0.10293333", "0.04815379", "0.08373292"] Total survival time for all animals given Poison III = [ Select ] ["4.42", "6.41", "8.12", "4.71", "8.71", "3.77", "9.88"] Average survival time for animals given Poison II and Medication C = [ Select ] ["0.3925", "0.4125", "0.544375", "0.375"]