According to a certain Mendelian genetic model, self-pollination of pink-flowered plants should produce progeny that are red, pink, and white in the ratio 1:2:1. A geneticist self-pollinated pink-flowered snapdragon plants and produced 234 progeny with 54 red, 122 pink and 58 white flowered plants. To test if these numbers indeed follow the model ratio, what should be an appropriate null hypothesis? A. P(Red) = 54/234, P(Pink) = 122/234, P(White) = 58/234. B. P(Red) = 54%, P(Pink) = 122%, P(White) = 58%. C. P(Red) = 1, P(Pink) = 2, P(White) = 1. D. P(Red) = 0.25, P(Pink) = 0.5, P(White) = 0.25. 2. What would be the degree of freedom for an appropriate test? A. 3 B. 2 C. 1 D. 0 3. If we fail to reject the null hypothesis at 0.05 significance level, what do you conclude? A. The self-pollinated plants of the geneticist do not follow the ratio 1:2:1 and this validates the model. B. The self-pollinated plants of the geneticist do not follow the ratio 1:2:1 and this contradicts the model. C. The self-pollinated plants of the geneticist indeed follow the ratio 1:2:1 and this validates the model. D. The self-pollinated plants of the geneticist indeed follow the ratio 1:2:1 and this contradicts the model.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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