Rationale

Cultivation theory proposes that repeated exposure to television content can shape viewers’ perceptions of social reality. If television frequently depicts people working in law enforcement, criminal justice, medicine, and emergency response, heavier viewers may perceive these occupations as more common in the population. This analysis examines whether television viewing is positively associated with estimates of the percentage of Americans employed in these occupations.

Hypothesis

People who spend more hours per week watching television will estimate that a larger percentage of the U.S. population works full time in the careers more frequently seen on television such as law enforcement/criminal justice, medicine, or emergency response services.

Variables and Method

I used data from 400 volunteers recruited from a random sample of U.S. adults. Their television viewing was tracked for six months, and they then estimated the percentage of Americans working full time in law enforcement/criminal justice, medicine, or emergency response. The independent variable, video, measures average weekly television hours. The dependent variable, pct, combines participants’ percentage estimates for these occupations. I ran a bivariate regression in R using a .05 significance threshold.

Results

People who watched more television tended to give higher occupational estimates. Each additional weekly viewing hour was associated with a predicted increase of about 0.84 percentage points (b = 0.844, p < .001). The model accounted for 31.11% of the variation in participants’ estimates (R² = .3111). These results support my hypothesis, but they do not prove that watching television caused people to give higher estimates.

## 
## Call:
## lm(formula = pct ~ video, data = cultivation)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -28.5917  -6.1607   0.6423   6.7433  23.8483 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 23.20761    2.20264   10.54   <2e-16 ***
## video        0.84400    0.06296   13.41   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.737 on 398 degrees of freedom
## Multiple R-squared:  0.3111, Adjusted R-squared:  0.3093 
## F-statistic: 179.7 on 1 and 398 DF,  p-value: < 2.2e-16

Here is the Code I used to create this document: