Now we can interpret this table.

First, let's look at the p-value.

The p-value is 0.567,

which is much larger than 0.05.

This means that the differences between

male and female Facebook usage time

is not statistically significant.

So coefficient here is 16,

which means that the differences between male

and female users usage time

is 16 minutes per day.

However, because the p-value is pretty high,

the coefficient becomes less meaningful.

The R-square is 0.0197,

which is about 0.02.

This means that only two percent of the variance in

the Facebook users time is accounted by gender.

Overall, this data does not provide

strong support to our hypothesis;

female users spend more time on Facebook than male users.

Again, this might seem overwhelming for those of

you who do not have

any experience in statistical analysis.

So if you want to know more about linear regression,

and you can take a statistic class. A takeaway.

Here are the steps to perform a quantitative analysis.

Form hypothesis, decide variable,

collect data, run statistical analysis.

Finally, interpret data and report the results.

Thank you for watching this video,

hope to see you in the next one.