Statistics 1

• The critical value is the first value to fall inside of the critical region
• A critical region is a region of the probability distribution which, if the test statistic falls within it, would cause you to reject the null hypothesis
• The null hypothesis H0 is the hypothesis that you assume to be correct
• The alternative hypothesis H1 tells you about the parameter if your assumption is shown to be wrong.
• A hypothesis is a statement made about the value of a population parameter
• The result of the experiment or the statistic that is calculated from sample is the test statistic
• Actual significance level of a hypothesis test is the probability of incorrectly rejecting the null hypothesis
• For two tailed tests, the critical region is made up of two parts, one at each end of the distribution.
• A census measures every member of a population
• Often, sampling units of a population are individuality named or numbered to form a list called a sampling frame.
• A variable that can take any value in a given range is a continuous variabl. Eg. Time
• A variable that can take only specific values in a given range is a discrete variable. Eg. Number of people
• Daily total rainfall is measured in mm. Amounts less than 0.05mm are recorded as “tr” or “trace”.
• Daily total sunshine is recorded to the nearest tenth of an hour.
• Daily mean wind speed is measured in knots over 24 hours, categorised according to the Beaufort scale.
• Wind direction is given as bearings and as cardinal (compass) directions.
• Daily maximum relative humidity is given as a percentage of air saturation with water vapour, above 95% is misty/foggy.
• Daily mean cloud cover is measured in oktas or eighths of the sky covered by cloud.
• Daily mean visibility is measured in decametres, and is the greatest horizontal distance at which an object can be seen in daylight.
• Daily mean pressure is measured in hectopascals (hPa). Any missing data is given an n/a.
• For mutually exclusive events, P(A or B)=P(A) + P(B)
• For independent events, P(A and B)=P(A) x P(B)
• You can model X with a binomial distribution, B(n, p), if;

  -there are fixed number of trials

  -there are two possible outcomes (success or failure)

  -there is a fixed probability of success, p

  -the trials are independent of each other
• A critical region is a region of probability distribution which if test statistic falls within it, would cause you to reject the null hypothesis.