Ontario Health Survey The Ministry of Health in the province of Ontario, Canada, wants to know whether the national health care system is achieving its goals in the province. Much information about health care comes from patient records, but that source doesn’t allow us to compare

people who use health services with those who don’t. So the Ministry of Health conducted the Ontario Health Survey, which interviewed a random sample of $61,239$ people who live in the province of Ontario.

(a) What is the population for this sample survey? What is the sample?

(b) The survey found that $76\%$ of males and $86\%$ of females in the sample had visited a general practitioner at least once in the past year. Do you think these estimates are close to the truth about the entire population? Why?

Given the sample size, $n=61239$

The Ontario Health Survey was undertaken by the Ministry of Health in the Canadian province of Ontario to see if the national health-care system was accomplishing its objectives in the province.

A simple random sample (SRS) of size $n$ is made up of $n$ people chosen from the population with an equal chance of being the sample that is actually chosen.

The Ministry of Health in Ontario aims to know if the national healthcare system is meeting its objectives in the province through the Ontario Health Survey. In a statistical study, the population refers to the complete group of people who need to know something. As a result, the population is mostly Ontario residents. A sample is a subset of the population from which we collect data. A random sample of $61239$ people living in was interviewed by the Ministry of Health Survey. As a result, the $61239$ people interviewed from the sample.

According to the Ontario Health Survey, $76$ percent of males and $86$ percent of females visited a general practitioner at least once in the previous year. A random sample of $61239$ people living in was interviewed by the Ministry of Health Survey. The sample should be picked at random and the sample size should be very large when reaching the conclusion. Because the sample size is substantial, the sample is a "random sample," and the sample has a large proportion of both sexes, it is reasonable to assume that the two figures are accurate reflections of the values for the entire population.