24 is the least common denominator
A histogram is better for "discrete" data and a frequency polygon is better for "continuous" data.
<h3>What is histogram?</h3>
A histogram is a data representation that looks like a bar graph and buckets a wide range of categories into columns all along horizontal x-axis.
- The numeric count or percentage of happenings in the data for every column is represented by the vertical y-axis.
- Columns can be employed to visualize data distribution patterns.
- Technical analysts use the MACD histogram in trading to making data in momentum.
- The MACD histogram columns could provide buy and sell signals earlier than the MACD and signal lines.
<h3>What is
frequency polygon?</h3>
Frequency polygons are a graphs depiction of the distribution that aids in data comprehension by utilizing a specific shape.
- Frequency polygons are comparable to histograms but are more beneficial when comparing two or more different data sets.
- The graph primarily displays cumulative frequency distribution data as a line graph.
- Frequency Polygons are a type of graph that deciphers information or data and are broadly used in statistics.
- This graphic form of data representation aids in the depiction of the data's shape and trend in a systematic and organized manner.
To know more about the histogram, here
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2) Add 0.1 to both sides. v/2.2=7.5
Then multiply by 2.2 on both sides.
v=16.5
4) Subtract 1.9 from both sides. -1.3g=-13
Divide both sides by -1.3
g=10
6) Add 1.4 to both sides. -12.9=-3d
Divide -3 on both sides.
d=4.3
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Answer:
Suppose we roll a six-sided number cube. Rolling a number cube is an example of an experiment, or an activity with an observable result. The numbers on the cube are possible results, or outcomes, of this experiment. The set of all possible outcomes of an experiment is called the sample space of the experiment. The sample space for this experiment is \displaystyle \left\{1,2,3,4,5,6\right\}{1,2,3,4,5,6}. An event is any subset of a sample space.
The likelihood of an event is known as probability. The probability of an event \displaystyle pp is a number that always satisfies \displaystyle 0\le p\le 10≤p≤1, where 0 indicates an impossible event and 1 indicates a certain event. A probability model is a mathematical description of an experiment listing all possible outcomes and their associated probabilities. For instance, if there is a 1% chance of winning a raffle and a 99% chance of losing the raffle, a probability model would look much like the table below.
Outcome Probability
Winning the raffle 1%
Losing the raffle 99%
The sum of the probabilities listed in a probability model must equal 1, or 100%.
