Notes

1st slide- title page, stand and look pretty make sure you don’t smell

2nd slide- comparing actual against predicted, logistic
-We first used the logistic model to predict the population if trends continued from the 1960-1980 data
-The predicted results remained at a steady growth, as fluctuations and external factors were not taken into account whereas the actual population size increased a lot more rapidly.

3rd slide- Malthusian Model
-Plotted a second graph which shows both actual results and the predicted results.
-As time increased from 1960 to 2010 the gap between the two sets of data increased greatly, the predicted results remained at an almost non apparent growth as fluctuations and external factors were not
taken into account whereas the actual population size increased a lot more rapidly.
-The Malthusian Growth Model may be accurate to a certain degree when estimating a population over a period of five years and under.


4th slide- time against percentage error
- ‘Malthusian Growth Model’ to the set of data France1b.xlsx
- Time increased the accuracy of the Malthusian model decreased.
- Level of accuracy calculated by finding the percentage error.
- By interpreting the graph, we can see that the percentage error increased linearly over time.
-As the percentage error increases, the validity of the results decreases thus rendering the Malthusian model inaccurate over a long period.

5th slide-
-repeated malthusian, this time with less data points
-data for every ten years was used rather than every single year
-results seemed a lot more accurate
-Malthusian model accuracy is dependent on the amount of data points used rather than the length of time being predicted as we had concluded earlier