Here are the essential concepts you must grasp in order to answer the question correctly.
Histogram
A histogram is a graphical representation of the distribution of numerical data, where the data is divided into intervals (bins) and the frequency of data points within each interval is represented by the height of bars. It helps visualize the shape, spread, and central tendency of the data, making it easier to identify patterns such as skewness or modality.
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Normal Distribution
A normal distribution is a continuous probability distribution characterized by its bell-shaped curve, where most of the observations cluster around the central peak and probabilities for values further away from the mean taper off symmetrically. Key properties include the mean, median, and mode being equal, and about 68% of the data falling within one standard deviation of the mean.
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Criteria for Normality
The criteria for determining if a dataset follows a normal distribution include visual assessments (like histograms), statistical tests (such as the Shapiro-Wilk test), and checking for symmetry and the absence of skewness. A strict interpretation requires that the data closely aligns with the properties of a normal distribution, which can be evaluated through these methods.
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Finding Standard Normal Probabilities using z-Table