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We want to test the hypothesis that the mean number of credit hours taken per semester by OSU undergraduates is less than 16 hours.  Therefore, we obtain a random sample of credit hours for 49 students. The sample mean is 15 hours and the sample standard deviation is 4 hours.  We want to test:    Ho:  μ = 16 hours    Ha:  μ < 16 hours using a significance level (α) = 0.01. What is the calculated value of the test statistic needed to test the null hypothesis in this problem?

We want to use a confidence interval to estimate the proportion of students in the College of Food, Agricultural, and Environmental Sciences that are female.  What sample size would be necessary if we want to estimate the true population proportion of female students correct to within 0.03 with probability 0.95?  In an earlier small-scale pilot study we obtained an estimate of the proportion of female students (p) that was equal to 0.48.

Scientists want to estimate the difference in twinning rate of two lines of beef cattle that have been selected for increased frequency of twin births.  Last spring, 40 of the 100 cows in Line 1 gave birth to twins.  In Line 2, 30 of the 100 cows gave birth to twins.  Find the point estimate of the true difference in population proportions of cows giving birth to twins in Lines 1 and 2.

The objects (people, plants, animals, or things) upon which the response variable is measured are called the ____________.

Graphical methods of describing qualitative data include

A perfect positive correlation between variables X and Y indicates that the correlation between these two variables is equal to __________.

The 25th percentile is also called the

The ____________ in an experiment are the factor level combinations that are utilized.

A random sample of 16 Standardbred horses was selected from a population of Standardbreds.  The mean time required for these 16 horses to run a mile while pulling a sulky was 130 seconds (i.e., 2 minutes and 10 seconds),  The standard deviation of the sample was 10 seconds. Construct a 90% confidence interval for the true population mean for racing time of the Standardbred horses.

A randomized block design is used to compare postweaning average daily gains of 4 breeds of beef cattle, Hereford, Angus, Charolais, and Simmental (we can think of the breeds at the “treatments”).  The breeds are divided into 3 weight classes (i.e., 3 blocks).  Block 1 contains cattle weighing 450 to 500 lb at the beginning of the experiment, block 2 contains cattle weighing 500 to 550 lb at the beginning of the experiment, and block 3 contains cattle weighing 550 to 600 lb at the beginning of the experiment.  The postweaning average daily gains (in pounds per day) are as follows:  Block Hereford Angus Charolais Simmental 1 3.50 3.60 3.70 3.75 2 3.55 3.63 3.71 3.80 3 3.56 3.62 3.80 3.90 The partially completed ANOVA table for this experiment is as follows: Source df SS MS F Total   .160     Breed   .139 .046 46 Block   .014 .007   Error   .007 .001   Calculate the F statistic for blocks. Do the block means differ (i.e., was blocking effective in removing variation in average daily gain)?  Use a significance level of α = 0.05.