In this project you look at the highest temperature on each of 30 days. You show it in a table and a graph, find the centre, the spread and the chances, and write a short report with a limit. The code boxes only need Run and a few changed numbers.
3 lessons, about 1 h 25 min3 simulations10 problems6 practice questionsPython in every lesson
A data project has six steps: ask one clear question, collect the data, clean it, show it, summarise it and report it. A month of daily highest temperatures is numerical data, measured, and a rainy day is a category. A frequency table counts the days in each group, and a line graph shows how the data changes over time.
The mean, the median and the mode find the centre. The range, the interquartile range and the standard deviation measure the spread. For the month, the mean is 30.7 degrees, the median is 31 degrees, and the modes are 30 and 31. The chance of a rainy day is estimated by its relative frequency, 10 out of 30, which also predicts how many rainy days to expect.
A report gives the question, the method, the numbers, a graph and one limit. Compare groups with their means, and say how many days are in each group. Rainy days in the month were cooler on average, 28.5 against 31.85 degrees, but the data shows an association, not a cause. A good report does not claim more than the data shows.
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