KIN 4310 1nd Edition Exam 3 Study Guide Lectures 16 22 Lecture 16 March 31 The independent t test is a hypothesis test that is used to determine if there is a significant difference between two groups The dependent t test is a hypothesis test that is used to determine if there is a significant difference between one group of subjects and they are tested under two conditions This test requires paired data and also two sets that are using the same measurement scale The three things you need are number of pairs of measurements the sum of all differences the sum of the squares of all the differences There are 5 steps Step 1 Calculate the t value for dependent means with the equation Step 2 After you know the t value you must determine the degrees of freedom Step 3 Determine the critical value of t by using table B2 in the textbook Step 4 Compare your t value to the critical value Step 5 Make a decision whether or not to reject HO or fail to reject HO An Analysis of Variance or ANOVA is a method for testing the hypothesis that three or more population means are equal We have to assume that each group is comprised of randomly selected sample the scores in each group are normally distributed and the variances of each group population are homogenous The ANOVA uses the F score which is variance between groups variance within groups The F distribution is not symmetric and is skewed positively The values of F can be 0 or positive The F distribution changes shape with respect to degrees of freedom Variance WITHIN Groups considers how spread out the data is in each group relative to its group mean Lecture 17 April 2 Variance BETWEEN Groups considers how spread out the group means are The total variance is based on all of the data from all of the groups Analyzing the F Statistic If there is no effect of the treatment the MSbetween will be relatively small and so F will small IF there is a significant effect of the treatment the MSbetween will be large relative to MSwithin and so F will be large If F is greater than the critical value of F then there is an effect of treatment and we can reject the null hypothesis Calculating F You will need the number of groups the total number of data points and the mean value of each group Then you will use an ANOVA table to calculate the sum os squares of all data the sum of squares within groups the sum of squares between groups and the degrees of freedom Once you find out the F value you will determine the critical value using table B3 in the textbook Lecture 18 April 7 A two way ANOVA also called the factorial ANOVA is similar to a one way ANOVA but there are two independent factors It is used when we want to learn about the main effects of each factor individually but we also what to understand how they interact In a two way ANOVA there are 3 things to differentiate against factors main effects and interaction effects A factor is a variable that separates data into groups o Ex Gender Male of Female o Ex Age Young middle aged elderly Main effects are when there is a significant difference between levels of a factor o Ex There is a main effect on gender and stature o Ex There is a main effect of age on BMI Interaction effects are when the effect of one factor depends on another factor o Ex There is an interaction between irrigation and fertilizer on tree growth Facts of ANOVA When the variance within groups decreases the variance between groups becomes more apparent When the variance between groups decreases the variance within groups becomes more apparent All ANOVA tests concern the right tail of the F distribution and a larger value of F represents a low probability that the data could have resulted if the null hypothesis is true Lecture 19 April 9 Correlation Studies allow us to determine the significance of the correlation To do this we need to determine the critical value of r by using Table B4 in the textbook If r is significant it Is reasonable to assume that it came from a population that was significant The r distribution has the values from 1 to 1 and you are more likely to get an r value that equals somewhere around 1 if the null is true and the population is uncorrelated Below are the correlation studies steps Step 1 Calculate test statistic r Step 2 Look up the critical value of r Step 3 Compare your r to the critical value Step 4 Reject the null hypothesis or fail to reject the null hypothesis Review Questions from class Which statement is true about the F distribution o It is used in analysis of variance The variance between groups represents o How much the group means vary with one another Lecture 20 April 14 Health is the absence of physical pain physical disability and conditions likely to cause death It also concerns emotional well being and satisfactory social functioning One can check their individual health status through observation by a physician or through a self report type survey One can check the health of a population by looking at life expectancy at birth death rate prevalence of disease and pollution Mortality This term deals with death It is the number of deaths in a population for a given period of time number of people in the population during that period of time Morbidity This term deals with disease Incidence deals with new diseases and it is the number of new cases of a disease in a period of time number of people in the population during a period of time Prevalence deals with how prevalent it is in a population and it is the number of cases of a disease in a population number of people in the population Disability Adjusted Life Years DALY This term is the number of years lost the number of years spent in a diseased state A large DALY represents a lot of mortality and morbidity Health and Fitness are related but they are different If you are fit you are able to fit in your environment and survive and thrive there There are 5 things that represent health related physical fitness only and they are Body composition Aerobic fitness Flexibility Muscular endurance Muscular strength Lecture 21 April 16 Body Composition is the term that describes the different components that make up the body such as fat muscle and bone and is important in assessing health status and disease risk We can assess body composition in two different approaches direct or indirect techniques Direct Techniques involve looking inside the body and measuring the different tissue by volume or area Some examples include o DXA o MRI o CT Indirect Techniques