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The table shows the changes in a city's average weekly temperature. Week Average Temperature (ºF) 1 24.4 2 24.8 5 26.1 8 27.2 15 30.1 24 33.6 The data shows a positive linear a negative linear an exponential an unrecognizable trend. Based on the table, we can assume that the city's average weekly temperature in the 26th week will be between 30.1 and 33.6 degrees be more than 33.6 degrees be less than 33.6 degrees not change .

The table shows the changes in a citys average weekly temperature Week Average Temperature ºF 1 244 2 248 5 261 8 272 15 301 24 336 The data shows a positive l class=

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MissPhiladelphia
The data shows a positive linear trend since the slope of the line calculated was 0.4 and it has an R^2 value of 0.9998 which proves its linearity. Based on the table, we can assume that the city's average weekly temperature in the 26th week will be be more than 33.6 degrees since the data shows a positive linear trend.

Answer:

Step-by-step explanation:

Given data is

The regression line shows a slope of 0.4 and y intercept as 24.029

i.e. since slope is positive, we find that when week increases temperature increases.

Regression equation is

[tex]y=24.029+0.4x[/tex]

Hence when week = 26,

we get

temperature = [tex]y=24.029+0.4(26)\\=24.029+10.4\\34.429[/tex]

Hence more than 33.6 degrees

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