Anova: Single Factor 3 SUMMARY 4 Groups Count Average Sum Variance 5 Pool 6 Bdrooms 38 38 144 3.789473684 1.413940256 8 9 ANOVA 10 Source of Variation 11 Between Groups 12 Within Groups 13 df 1 272.8421053 385.9315895 74 0.706970128 F crit 3.97022958 MS P-value 272.8421053 52.31578947 4.4135E-31 14 Total 325.1578947 75 1 Anova: Single Factor 3 SUMMARY Count Average 4 5 Pools Groups Sum Variance 67 67 1 6 Bedroom 67 255 3.805970149 2.764812302 8 9 ANOVA 10 Source of Variation 11 Between Groups 12 Within Groups 13 P-value 2.095E-27 df F crit SS 263.761194 182.4776119 MS 190.7986259 3.912875028 263.761194 132 1.382406151 14 Total 446.238806 133
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.
Is there a difference in the average number of bedrooms in houses with pools as compared to houses without pools? Use alpha = 0.05.
First attached image is the anova calculations with houses with no pools, second image is houses with pools. Looking for clarification on how it is compared
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