2025-04-12

Hypothesis Testing

  • The topic that is being presented is called Hypothesis testing.This type of statistical tactic is to make a good decision about population based on the sample data that you are given.

  • To start, always open with a “hypothesis” on what you can tell based on a data set given. A very simple example is how many men and women have job in the city. So you would take this sample and can estimate from there what women and men are employed and unemployed.

Basic Idea of Hypothesis Testing

  • Null hypothesis: This is a prediction that does not have any importance to the given variables in the data set. So it is just a random hypothesis to give a basis of the estimate a scientist is making. Always start with this step first. This hypothesis is always set to be true.

  • Alternative Hypothesis: This is to counter you null hypothesis. This will prove is the null hypothesis you gave in your first step will always be true. The alternative hypothesis is always proven to be false so yu can have a better argument for your null hypothesis.

Continuing with Basic Idea of Hypothesis Testing

  • Always collect data from the sample you are given. This will be the start of you making more guesses to have a better understanding with the data.

  • Analyze your data using any statistical tools that you might have been given in your research project to prove that your hypothesis is legit.

  • Lastly, make your decision on where you want yoir hypothesis to go in your research.

Ploty Plot example of a Hypothesis Testing

Analysis on Grap

The weather shown throughout the six days show the influx in the temperature throughout the week. You can see with this data that the temprature drops on Wednesday and goes back up Saturday.

Percipitation of the Week

Analysis on Bar Graph

The percentage of rain fall seems a bit consistant throughout the whole week. The chances of rain seems very little.

Wind This Week

Analysis on the Wind

This week seems to be the most windy as the week goes on.

Converting Fahrenheit to Celsius

\[ celsius = \frac{5}{9}(fahrenheit - 32) \]

Intesnsity of the Rain Fall

\[ intensity = \frac{percipitation}{hours} \]

Code that Created the Plotly Plot

tempHigh = c(61, 68, 64, 55, 61, 67, 78) tempLow = c(48, 57, 44, 39, 45, 61, 54) dayOfWeek = c(‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’)

fig <- plot_ly() fig <- fig %>% add_trace(x = dayOfWeek, y = tempHigh, type = ‘scatter’, mode = ‘lines+markers’, name = ‘Temp High’, line = list(color = ‘red’)) fig <- fig %>% add_trace(x = dayOfWeek, y = tempLow, type = ‘scatter’, mode = ‘lines+markers’, name = ‘Temp Low’, line = list(color = ‘blue’)) fig <- fig %>% layout(title = “Weather For The Week in Maryland”, xaxis = list(title = ‘Day of the Week’, categoryorder = ‘array’, categoryarray = dayOfWeek), yaxis = list(title = ‘Temperature (Fahrenheit)’))

fig