The median is 9 (or between 10-15 if it is a histogram) and mean (if you don't spend a lifetime to calculatemean) or you can mention and mean is lower or higher than median if it is right skewed or left skewed. Leave room for mode or for detailedcalculation of mean etc.
The mean weight, proportion of all items, be specific, 500 gm butter packs, 300 ml milk bottles, percentage of soccer players in club A, proportion of heart patients in the city hospital). Use population parameters whenever possible, but can also use sample statistics.
It is given that these are random samples. It is reasonable to assume that the samples are independent since both samplesarelargeenough (>=30) so that the Central Limit Theorem applies making it approximatelynormal and it is reasonable to assume that the sample size are less than the 10% of the population
What happens if you see that only 50% of your sample items fall in your 95% confidence range
That is perfectly fine as we are estimating sample mean, not individual items. We don't mean that 95% of individual items should fall within Confidence Interval. Also, there is no guarantee that the true population mean will be in this interval, but mostly it is true (so plausible is a better term)
The sample is random. The sample size is >=30, so the central limit theorem can be applied making the sampling distribution approximately normal. Reasonable to assume that the sample size is less than 10% of the population, making it independent.
Why you would accept or reject the null hypothesis. Probability of type 1 error, type 2 error [basically probability that the value falls where null hypothesis is accepted]. Language - There is sufficient evidence to reject Ho or we don't have sufficient evidence to reject Ho