Art of Stat: Regression
ASO Keyword Dashboard
Tracking 43 keywords for Art of Stat: Regression in Google Play
Art of Stat: Regression tracks 43 keywords (1 keyword ranks; 42 need traction). Key metrics: 0% top-10 coverage, opportunity 71.2, difficulty 44.5, best rank 26.
Simple & Multiple Linear Regression, Logistic Regression, Inference & Prediction
Tracked keywords
43
1 ranked • 42 not ranking yet
Top 10 coverage
0%
Best rank 26 • Latest leader —
Avg opportunity
71.2
Top keyword: summary
Avg difficulty
44.5
Lower scores indicate easier wins
Opportunity leaders
- 63.7
summary
Opportunity: 75.0 • Difficulty: 51.8 • Rank —
Competitors: 259
- 61.3
module
Opportunity: 74.0 • Difficulty: 37.3 • Rank —
Competitors: 115
- 63.4
response
Opportunity: 74.0 • Difficulty: 39.3 • Rank —
Competitors: 285
- 64.0
example
Opportunity: 74.0 • Difficulty: 41.1 • Rank —
Competitors: 443
- 59.8
mean
Opportunity: 74.0 • Difficulty: 39.9 • Rank —
Competitors: 307
Unranked opportunities
summary
Opportunity: 75.0 • Difficulty: 51.8 • Competitors: 259
module
Opportunity: 74.0 • Difficulty: 37.3 • Competitors: 115
response
Opportunity: 74.0 • Difficulty: 39.3 • Competitors: 285
example
Opportunity: 74.0 • Difficulty: 41.1 • Competitors: 443
mean
Opportunity: 74.0 • Difficulty: 39.9 • Competitors: 307
High competition keywords
simple
Total apps: 254,597 • Major competitors: 11,042
Latest rank: — • Difficulty: 55.8
way
Total apps: 205,299 • Major competitors: 10,421
Latest rank: — • Difficulty: 56.5
data
Total apps: 180,122 • Major competitors: 6,587
Latest rank: — • Difficulty: 57.6
check
Total apps: 135,668 • Major competitors: 7,069
Latest rank: — • Difficulty: 58.0
multiple
Total apps: 129,574 • Major competitors: 8,197
Latest rank: — • Difficulty: 56.5
All tracked keywords
Includes opportunity, difficulty, rankings and competitor benchmarks
| Major Competitors | |||||||
|---|---|---|---|---|---|---|---|
| explanatory | 71 | 100 | 31 | 50 1,454 competing apps Median installs: 1,212 Avg rating: 1.7 | 26 | 26 | 34 major competitor apps |
| art | 70 | 100 | 51 | 75 50,171 competing apps Median installs: 2,063 Avg rating: 1.9 | — | — | 2,977 major competitor apps |
| version | 70 | 100 | 56 | 76 56,833 competing apps Median installs: 3,752 Avg rating: 2.2 | — | — | 3,125 major competitor apps |
| way | 66 | 100 | 57 | 85 205,299 competing apps Median installs: 1,661 Avg rating: 2.0 | — | — | 10,421 major competitor apps |
| multiple | 67 | 100 | 56 | 81 129,574 competing apps Median installs: 2,393 Avg rating: 2.0 | — | — | 8,197 major competitor apps |
| install | 70 | 100 | 50 | 76 58,944 competing apps Median installs: 2,495 Avg rating: 2.0 | — | — | 2,542 major competitor apps |
| legacy | 73 | 100 | 37 | 57 4,042 competing apps Median installs: 1,641 Avg rating: 2.1 | — | — | 197 major competitor apps |
| news | 69 | 100 | 51 | 78 81,070 competing apps Median installs: 1,049 Avg rating: 1.8 | — | — | 2,201 major competitor apps |
| simple | 66 | 100 | 56 | 86 254,597 competing apps Median installs: 1,723 Avg rating: 1.8 | — | — | 11,042 major competitor apps |
| color | 69 | 100 | 51 | 77 64,334 competing apps Median installs: 2,273 Avg rating: 2.0 | — | — | 4,080 major competitor apps |
| original | 71 | 100 | 52 | 72 33,699 competing apps Median installs: 4,910 Avg rating: 2.2 | — | — | 2,538 major competitor apps |
| check | 67 | 100 | 58 | 82 135,668 competing apps Median installs: 1,710 Avg rating: 2.0 | — | — | 7,069 major competitor apps |
| useful | 70 | 100 | 48 | 75 53,299 competing apps Median installs: 2,975 Avg rating: 1.9 | — | — | 2,424 major competitor apps |
| display | 70 | 100 | 52 | 76 56,007 competing apps Median installs: 1,297 Avg rating: 1.8 | — | — | 2,181 major competitor apps |
| data | 67 | 100 | 58 | 84 180,122 competing apps Median installs: 1,181 Avg rating: 1.8 | — | — | 6,587 major competitor apps |
| future | 70 | 100 | 48 | 76 55,685 competing apps Median installs: 1,187 Avg rating: 1.9 | — | — | 2,134 major competitor apps |
| confidence | 73 | 100 | 51 | 68 19,030 competing apps Median installs: 822 Avg rating: 1.8 | — | — | 640 major competitor apps |
| summary | 75 | 100 | 52 | 64 9,964 competing apps Median installs: 1,352 Avg rating: 1.8 | — | — | 259 major competitor apps |
| log | 71 | 100 | 47 | 73 40,315 competing apps Median installs: 1,056 Avg rating: 1.9 | — | — | 1,769 major competitor apps |
| standard | 72 | 100 | 48 | 69 22,035 competing apps Median installs: 2,277 Avg rating: 2.0 | — | — | 1,160 major competitor apps |
| module | 74 | 100 | 37 | 61 6,999 competing apps Median installs: 960 Avg rating: 1.6 | — | — | 115 major competitor apps |
| model | 73 | 100 | 46 | 66 14,483 competing apps Median installs: 2,649 Avg rating: 1.9 | — | — | 775 major competitor apps |
| additional | 70 | 100 | 53 | 74 46,882 competing apps Median installs: 2,952 Avg rating: 2.1 | — | — | 2,651 major competitor apps |
| response | 74 | 100 | 39 | 63 9,538 competing apps Median installs: 1,019 Avg rating: 1.8 | — | — | 285 major competitor apps |
| study | 70 | 100 | 48 | 75 53,407 competing apps Median installs: 1,139 Avg rating: 1.7 | — | — | 1,145 major competitor apps |
App Description
Simple & Multiple Linear Regression, Logistic Regression, Inference & Prediction
The new Art of Stat app includes this Art of Stat: Regression module and many others useful for statistics and data science. Please install the new Art of Stat app now.
However, this legacy version will continue to work
**********************
Original Description:
The Art of Stat: Linear Regression app creates scatterplots, fits simple (and multiple) linear, logistic or exponential regression models, and displays inference for model parameters (standard errors, confidence intervals, P-values).
New: The app now also fits multiple linear regression models and allows including categorical predictors and two-way interactions!
The app computes and displays confidence intervals for the mean response and prediction intervals for a future response. The fitted model and the intervals are visualized on the scatterplot, and you can obtain and plot raw and standardized residuals.
You can color points on the scatterplot according to a third quantitative or categorical variable to reveal additional patterns.
For data entry, you can enter your own data via the new Data Editor app, import a CSV file, or choose from several pre-loaded example datasets.
Features:
- Scatterplot Matrix to study pairwise relationships
- Display the fitted regression equation on the scatterplot, even when including (and additional) categorical predictor
- Table with all regression coefficients and their inferences (P-values, confidence intervals)
- Summary statistics such has R^2, R^2-adjusted and maximized Log-Likelihood
- Fitted values and (standardized) residuals (which you can download)
- Predictions for your own values of the explanatory variables
- Residual plot to check assumptions and for outliers
- lets you make predictions for your own values of the explanatory variables
- constructs a residual plot to check assumptions and for outliers