I shall reject the null hypothesis that " The coin is fair" at even 80% confidence level.Edward S said:
A confidence level is a measure of the certainty or probability that a hypothesis or claim is true. It is typically expressed as a percentage and represents the likelihood that the results of an experiment or study are accurate.
The confidence level is directly related to the likelihood of rejecting the hypothesis of a fair coin. A higher confidence level means there is a lower probability of rejecting the hypothesis, while a lower confidence level means there is a higher probability of rejecting the hypothesis.
The significance level, also known as alpha, is the threshold at which a hypothesis is rejected. It is typically set at 5% or 0.05, meaning that if the probability of obtaining the observed results by chance is less than 5%, the hypothesis is rejected. In the case of a fair coin, a significance level of 0.05 would mean that if the probability of obtaining the observed results by chance is less than 5%, we can reject the hypothesis that the coin is fair.
A p-value is a statistical measure that represents the probability of obtaining the observed results by chance. In the case of a fair coin, a p-value of less than 0.05 would indicate that there is a less than 5% chance of obtaining the observed results if the coin is fair. This would lead to the rejection of the hypothesis of a fair coin.
The confidence level can be affected by several factors, such as the sample size, the variability of the data, and the chosen significance level. A larger sample size and lower variability can lead to a higher confidence level, while a smaller sample size and higher variability can result in a lower confidence level. Additionally, a higher significance level can increase the likelihood of rejecting the hypothesis, while a lower significance level can decrease it.