How can I measure bee and wasp population?
Short Answer 

No. You cannot appropriately examine population dynamics using the approach you've described.

You can, however, examine how foraging frequencies vary/correlate with field spraying (though this might take more effort than you're looking for).

 Long Answer 

You're not going to be able to properly quantify population levels from casual observance. 


Because you would be unable to effectively identify individuals, you would be unable to know if you're seeing different individuals or repeats of previous individuals. 
The data are also biased toward those species or individuals that use the habitat features in your particular garden and are biased against those that do not (Parsons &amp; Szewczak, 2009).
Further, you would have no way to identify which hives/nests that individuals are coming from (without watching them leave the nest directly), so you would not know which populations are represented at any given sighting. 


Unfortunately, although the question you link to (How best to count bees entering and leaving a hive to measure hive activity?) would allow you to better examine/compare separate populations, those methods likewise suffer from the same shortcomings listed above. 



What you can figure out:

Your causal observance can at best be used to quantify foraging frequency in your garden. 


In other words, you would just be able to count how many bees visit your garden at any given time and compare those values at different discrete time points. You could compare this to a number of environmental variables to look for trends. 


In your case, your approach would look something like the following:


You could count the number of sightings (or landings or feedings) in various random locations throughout your garden. 


Each of these locations should be randomly selected, and you would preferably collect numerous random samples from each of various "habitats" (i.e., different locations, different flowers, etc.).
You must return to the same locations each time and spend the same amount of time at each location each sampling period. 

You can do simple statistics on these different samples across all sampling periods to examine foraging frequency trends across time. 
If you directly measure a number environmental variables (e.g., temp., precipitation, humidity, cloudiness, etc.) you'll be able to rule out variance in your data due to these factors. 


Proper background research would be required to determine which variables might be important to measure.

Finally, you could do regression/ANOVA analyses to examine any correlation between nearby field spraying on your foraging activity.


However, there are a ton of variables that could affect the trends you see, so final analyses will likely be weak at best. 


Measuring those aforementioned environmental variables will help with this, as will increasing your sampling rate. See Power Analysis


  Power analysis is an important aspect of experimental design. It allows us to determine the sample size required to detect an effect of a given size with a given degree of confidence. Conversely, it allows us to determine the probability of detecting an effect of a given size with a given level of confidence, under sample size constraints. If the probability is unacceptably low, we would be wise to alter or abandon the experiment.





Note: Work by J.E. Eckert (1933) showed that (honey)bees can travel multiple miles from their hive/nest, so unless those fields are mutliple miles away, any pesticides could very well impact the populations visiting your garden.  



Another Option:

You could perform Trap Counts to try to approach quantifying populations rather than just quantifying foraging behavior.


This method is used frequently for other insects. However, I found very few reputable sources examining bees/wasps.


One example: Danka &amp; Gary (1987) estimated foraging populations effectively, but they did so by collecting data at the hive entrance. 

Though there is an inherent issue with trap studies as well:


As Petrovskii et al (2012) point out:


  Traps are effective at providing relative counts that enable comparisons but are poor at delivering information on the absolute population size.

However, Petrovskii et al (2012) show that a ‘mean-field’ diffusion model is capable of revealing the generic relationship between trap catches and population density.


Their paper is freely available here.




Citations


Danka, R. G., &amp; Gary, N. E. (1987). Estimating foraging populations of honey bees (Hymenoptera: Apidae) from individual colonies. Journal of economic entomology  80(2): 544-547.
Eckert, J. E. (1933). The flight range of the honeybee. Journal of Agricultural Research 47:257-285.
Parsons, Stuart and Joseph M. Szewczak (2009). Detecting, Recording, and Analyzing the Vocalizations of Bats In: Ecological and Behavioral Methods for the Study of Bats. Thomas H. Kunz and Stuart Parsons, ed. The Johns Hopkins University Press, Maryland, 2nd ed., pp. 91-111.  
Petrovskii, Sergei, Daniel Bearup, Danish Ali Ahmed, Rod Blackshaw (2012). Estimating insect population density from trap counts. Ecological Complexity 10: 69-82. http://dx.doi.org/10.1016/j.ecocom.2011.10.002.