The average monthly rainfalls in both Mt. Washington, New Hampshire and Quillayute, Qulimte Washington are shown in the dotplots below. Mit. Washington Source: National Climatic Data Center, http://lwf.ncdc.noaa.gov/oa/dlimate/online/c cd/nrmlprcp.html 15 13 12 14 10 11 9 2 nches of rain per month a) What does each dot represent? (Hint: How many dots are on each graph?) onthly Rantals There ore 12 b) What was the lowest monthly rainfall recorded for a month in Quillayute 2 c) What was the highest monthly rainfall recorded for a month in Mt. Washington? I0 Q=243 L4+4 o to +12+ 14 515712- 8.58-he neon for W-748008+8+8+8+9 +9+9 +9 +1012- 342 - e maon oe d) Calculate the mean amount of monthy rainfall for each town. Qu rog te Calculate the median amount of monthly rainfall for each town. (It may help to write the data values in a list first.) e) Q= 2,3, 1 1011,121415,\51+10/2- 8.5 w-7,8,8,8,82.6 8/2-8 f) Calculate the IQR for each town. 03-01 Q OI 474-4 03-12+14 13 13-4-9 ,2 2 W-01-818-8 03 - -9 9-8-1 2 g) Draw horizontal boxplots for this data Quallayuhe HOH Mt.Washington 15 13 14 12 11 10 2 3y inches of rain per month h) Suppose you were given the standard deviations for these towns plus two more, but you spilled your drink and can no longer read the names of the Options Summary statistics: Std. dev. towns. Which standard deviation is most reasonable for Quillayute? For 7.2111026 Mt. Washington? Explain. 0.79296146 4.8328108 0
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
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