Apply principles and procedures related to central tendency

Complete problems that apply principles and procedures related to central tendency, variability, and probability.
When data is collect as part of the research process, the scores fall in some sort of order.

Apply principles and procedures related to central tendency
Complete problems that apply principles and procedures related to central tendency, variability, and probability.
When data is collect as part of the research process, the scores fall in some sort of order. Central tendency talks about the center of the distribution, while variability discusses the spread of scores within the distribution. The scores from particular survey instruments can be converted to standard scores to increase the understanding among and between researchers as well as to further describe how they fall within the distribution.

Many statistical analyses use an assumption that data falls in a normal distribution. In this assessment, you will examine the normal curve as well as the area under the curve as it relates to standard scores.

Probability examines the likelihood of an event occurring. In this assessment, you will look at probability as well as binomial distribution.

This assessment focuses on measuring central tendency, especially the characteristics and calculating the mean, median, and mode. It will also help you practice your skills in variability, which is measure by range and standard deviation. The assessment also focuses on probability, which is the likeliness of a specific instance occurring.

More details;

Measures of Central Tendency
Measures of Central Tendency provide a summary measure that attempts to describe a whole set of data with a single value that represents the middle or centre of its distribution. There are three main measures: the mean, the median and the mode.
When data is normally distribute, the mean, median and mode should be identical, and are all effective in showing the most typical value of a data set.
It’s important to look the dispersion of a data set when interpreting the measures of central tendency.

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