A student was supplied with a stop watch, two metre rules and a simple pendulum suspended from a ceiling and was asked to measure the height of the ceiling indirectly. He set the pendulum swinging through a small angle and measured the period of oscillation for different lengths of the pendulum. Since he was unable to measure the length of the pendulum directly, he measured the height of the centre of the pendulum bob above the floor. He obtained the results tabulated below. Height of bob above floor (mm) Time for 50 oscillations (s) 400 155.3 600 148.8 800 142.2 1000 134.0 1200 127.4 1400 119.2 1600 110.5 The period T of the pendulum of length l is given by T = 2n (1) where g is the acceleration due to gravity. But l = H – h where H is the height of the ceiling and h is the height of the centre of the pendulum above the floor. Therefore (H – h) T = 2n Plot a suitable graph to find the height of the ceiling H from the two intercepts using linear regression to fit the best straight line through the data points. Assume that g = 9.8 ms-2 (g could be obtained from the slope of the graph). Having obtained your values for H, answer the following questions: (a) Which value of H do you consider to be the least accurate? Give reasons for your choice and explain how the accuracy could have been improved. (b) Why was the bob set swinging through a small angle?
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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Please read the question properly. It's specifically asking for linear regression to be used. Also, please remember the graph.
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