Frequency refers to the count of occurrences for each category, while percent represents the proportion of each frequency relative to the total number of observations, expressed as a percentage. Valid percent excludes any missing or invalid responses, giving a clearer picture of the data that is actually analyzed. Cumulative percent sums the valid percentages progressively, showing the total percentage up to and including each category, which helps in understanding the distribution of responses.
A cumulative frequency polygon has straight lines connecting the points. A normal cumulative frequency diagram uses a smooth curve to join the points.
frequency plot - number of counts relative frequency - number of counts/ total counts cumulative frequency - number of counts that are cumulatively summed cumulative relative frequency that are cumulatively summed. Examples: Let y = accidents per day for one week, and x = days of the week (1 to 7) y = (0, 0, 1, 2, 1, 5,1) for X = 1, 2, ... 7 frequency counts y = (0,0, 0.1,0.2,0.1, 0.5, 0.1) relative frequency y = (0,0,1,3,4,9,10) = cumulative frequency y = (0, 0, 0.1,0.3,0,0.4,0.9,1) cumulative relative frequency
it shows the realtive distinction between a varied set of data. the bars show wight, not height
what is the difference between a regular histogram and a percent frequency polygon
The difference between frequency polygon and line graphs is their purpose. Frequency polygons are for understanding shapes distributions, while line graphs shows information that is related in some way.
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A cumulative frequency polygon has straight lines connecting the points. A normal cumulative frequency diagram uses a smooth curve to join the points.
The first is more commonly used and, in a usual graph, goes from bottom left to top right. The second goes from top left to bottom right. Both are equally valid.
Cummulative is a misspelling. The word should be spelled cumulative.
frequency plot - number of counts relative frequency - number of counts/ total counts cumulative frequency - number of counts that are cumulatively summed cumulative relative frequency that are cumulatively summed. Examples: Let y = accidents per day for one week, and x = days of the week (1 to 7) y = (0, 0, 1, 2, 1, 5,1) for X = 1, 2, ... 7 frequency counts y = (0,0, 0.1,0.2,0.1, 0.5, 0.1) relative frequency y = (0,0,1,3,4,9,10) = cumulative frequency y = (0, 0, 0.1,0.3,0,0.4,0.9,1) cumulative relative frequency
Frequency has a 'Q' in it.
Cumulative is formed by the addition of new material of the same kind. Comprehensive is covering completely or broadly.
To calculate the median using linear interpolation in an O-give curve, first identify the total number of observations (N) and find the median position, which is ( \frac{N + 1}{2} ). Locate this position on the cumulative frequency curve (O-give) and determine the corresponding cumulative frequency value. If the median position falls between two cumulative frequency points, use linear interpolation to estimate the median value by finding the x-values (data points) associated with these frequencies and applying the formula for interpolation.
Identify the difference between primary sector and secondary sector
Continuous refers to measurements that can take any value, possibly between two limits. Cumulative usually refers to a count "up to and including" the current value.
It shows the correlation presented between the frequency something was brought ( or what ever it is that is being measured,) and compare this to how much/ often this was sold, made, etc.
it shows the realtive distinction between a varied set of data. the bars show wight, not height