The.sims.4.update.only.v1.91.186.inclu.first.fi... -

The Sims 4 (released August 30, 2022) is a base game update primarily focused on fixing pronoun-related bugs and introducing a new tutorial system through Scenarios. This update is often bundled with the First Fits Kit , which adds child-focused fashion items like trendsetting playdate outfits. Key Highlights of Update v1.91.186

Addressed several "High School Years" bugs, including issues with and early graduation diplomas . Improved camera behavior on macOS Monterey . Included Content: The Sims 4 First Fits Kit The.Sims.4.Update.Only.v1.91.186.Inclu.First.Fi...

The update is frequently paired with this kit, which focuses on fashion for Child Sims. Items included typically feature: The Sims 4 (released August 30, 2022) is

Developers tuned down the frequency of Sims constantly using their phones. Bug Fixes: The Sims 4 (released August 30

As with birth rates, we use data for 4 categories of countries from 1990 to 2015 (100 observations total). We have two explanatory variables, AGE and Y, where AGE is defined as the percentage of the population aged over 65 and Y is per capita GDP.

After eyeballing the scattergrams, we test the following functional form:

d = (minY^a)/Y^a * (1/AGE^g)

Where minY is the constant equal to the smallest value of Y in the series.

Logarithmic transformation gives:

ln(d) = ln(minY^a) – a*ln(Y) – g*ln(AGE)

which we test on the data using OLS. Here are the results:

Adjusted R square: 75.191

Intercept coefficient: 7.37384
t-Stat: 20.4011

Y coefficient: -1.01444
t-Stat: -13.1059

AGE coefficient: 2.0097
t-Stat: 11.5208

The estimated intercept is a good, but not perfect, approximation of ln(minY^a)

Here are the fitted against actual values of the scattergram for death rate against per capita GDP:

While the results are not as good as with the birth rates calculations, it is nevertheless a good enough fit and the explanatory variables have a strong enough confidence factor to be usable in our estimations.

We begin by examining the scatter of data for 100 observations of per capita GDP and per capita emissions for 4 categories of countries, over 25 years (1990 – 2015).

The scatter suggests a cubic functional form, so we test:

GHG = a + b*Y + c*Y^2 + d*Y^3

where GHG are per capita emissions of GHG, and Y is per capita GDP.

The results from OLS regression are:

Adjusted R square: 0.980438073

coefficient a: 1090
t-stat a: 3.06

coefficient b: 0.709310153
t-Stat b: 8.241453

coefficient c: -0.0000047025
t-Stat c: -1.01233

coefficient d: -0.000000000105314
t-Stat d: -1.47005

While the t-scores on the squared and cubed terms are low, the number of observations are also limited.

Here is the plot of the fitted against actual values: