you explain how to solve this question? If there is an equation that I can use will be appreciated.
70% of students answered question A correctly, 55% of students answered question B correctly, 20% of students answered neither question correctly. What is the percentage of students answered both question A and B correctly?
statistical parodies
In statistics, Xi represents an individual data point or observation within a dataset. It is commonly used to denote the ith data point in a sequence of data. The subscript i is used to differentiate between different data points in the dataset, with i typically ranging from 1 to n, where n is the total number of data points. Xi is a fundamental concept in statistical analysis and is essential for calculating various statistical measures and conducting data analysis.
A statistical question is one that anticipates variability in the data and seeks to gather information to analyze that variability. Unlike a simple question with a definitive answer, a statistical question typically requires data collection and statistical methods to answer. For example, "What is the average height of students in a school?" is a statistical question because it involves measuring and analyzing the heights of multiple students.
Random error.
A statistical question is one that anticipates variability in the data and can be answered by collecting and analyzing data. It typically involves a population or a sample and is designed to yield insights based on statistical methods. For example, asking "What is the average height of adult men in a city?" is a statistical question because it considers variations in height among individuals. In contrast, a non-statistical question would be one with a definitive answer, such as "What is the height of the tallest man in the world?"
What do you mean by Marginal probailities under statistical dependence
casual observation
There is no statistical term such as "deviation mean".
Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.Skew is a statistical function. It is used to indicate the asymmetry of a set of values around the mean of those numbers.
a row means an observation if there are many rows.
statistical parodies
Yes
Yes
Yes
25 x36 = 900 13 x 32 = 416 13 x 40 = 520 ----- 936 936-900 = 36 (13th observation)
A countable or measurable observation is referred to as a "quantitative observation." This type of observation involves data that can be expressed numerically, allowing for statistical analysis and comparison. In contrast, qualitative observations are descriptive and subjective, focusing on characteristics that cannot be measured numerically. Quantitative observations are essential in scientific research for drawing objective conclusions.
No. One observation will normally get you onevalue, not a set of values. Also, to be precise, the observation is the act of observing; the value is the result of the observation, not the observation itself.