The accompanying information is a set of coded experimental data on the compressive strength of a particular alloy at various values of the concentration of some additive. Complete parts (a) and (b) below Click the icon to view the compressive strength data. (a) Estimate the quadratic regression equation μyx = ßo +ß₁×₁ +ß₂ײ. (Round the constant to two decimal places as needed. Round all other constants and coefficients to three decimal places as needed.) (b) Test for lack of fit of the model. State the null and alternative hypotheses. Ho H₁ Determine the test statistic. f= (Round to two decimal places as needed.) Determine the P-value. P-value= (Round to three decimal places as needed.) State the conclusion. Ho. There sufficient evidence to conclude that a cubic model would fit the data better than a quadratic model. there is no lack of fit for the model. an exponential model would fit the data better than a quadratic model. a linear model would fit the data better than a quadratic model. there is a lack of fit for the model. Bearing Data Concentration, Compressive Strength, x y 10.0 25.1 10.0 27.1 10.0 28.8 15.0 29.6 15.0 31.3 15.0 27.5 20.0 31.1 20.0 32.7 20.0 29.7 25.0 31.8 25.0 30.4 25.0 32.1 30.0 29.1 30.0 30.6 30.0 32.7

Read through this scenario and look at the data that was collected.  State the null and all possible research hypotheses.  Review the results below (I used SPSS) and answer the questions that follow. Scenario:  A researcher wants to see if gender and / or income affects the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help.  The independent variables are gender, income, and the interaction of gender and income.  The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affects the total amount of help offered.  Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA.  His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect.  The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables…

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Many questions in research can be expressed as two competing statements about the population parameter. These two statements are called the null and the alternative hypotheses. Usually, the researcher hopes the sample evidence will be in favor of the alternative hypothesis, the new theory. It is important to be able to state the theories that are being put to a test.  Write out the hypotheses to be put to the test and define the parameter of interest in context of the problem.      Do a minority of Michigan residents clear snow from sidewalks before 9 am after snow has fallen?For this scenario, write out the hypotheses to be put to the test and define the parameter of interest in context of the problem. H0:Ha: The parameter p represents ___(provide appropriate definition in context)________