A/B Testing Test

Q: What topics are covered in the A/B Testing Test?

A/Bテストの設計 データ分析 A/Bテスト統合 A/BテストWebアプリケーション A/Bテスト変換

About the test:

A/Bテストテストでは、A/Bテストの方法論に関する候補者の知識と、データ駆動型の決定を下すためにデータを分析および解釈する能力を評価します。統計的概念、実験設計、仮説検査、およびデータ分析手法の理解を評価します。

Covered skills:

A/Bテストの設計
A/Bテスト統合
A/Bテスト変換

データ分析
A/BテストWebアプリケーション

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9 reasons why

Adaface A/B Test is the most accurate way to shortlist データアナリストs

Reason #1

Tests for on-the-job skills

The A/B Testing Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

A/Bテストの設計と実装
データを分析して、意味のある洞察を引き出します
A/Bテストをさまざまなシステムに統合します
A/Bメソッドを使用したWebアプリケーションのテスト
A/Bテストを使用したコンバージョンの最適化

Reason #2

No trick questions

Traditional assessment tools use trick questions and puzzles for the screening, which creates a lot of frustration among candidates about having to go through irrelevant screening assessments.

View sample questions

The main reason we started Adaface is that traditional pre-employment assessment platforms are not a fair way for companies to evaluate candidates. At Adaface, our mission is to help companies find great candidates by assessing on-the-job skills required for a role.

Why we started Adaface

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Reason #3

Non-googleable questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

これらは、10,000以上の質問のライブラリからのわずかなサンプルです。これに関する実際の質問 A/Bテストテストグーグルできません.

🧐 Question
Medium Hiring Developer Skewed Data Graph	Try practice test
Two companies A and B hired developers from the year 2001 to 2005. The given bar graph shows the hiring details. Now select the statements that are true based on the given details. A: The data given for Company A is skewed to the left. B: The data given for Company B is skewed to the right. C: The data given for Company A is skewed to the right. D: For Company B, mean and mode are equal. E: For Company B, mean is equal to median but less than mode. F: For Company A, median is less than mode but greater than mean.
Medium Negative correlation	Try practice test
Saffi, one of the popular schools in San Francisco did a school wide study of the students in middle school. The study found that there is a negative correlation between the time spent on Facebook per day by students and their academic achievement. How can we understand the results of this study? A: An increase in time spent on Facebook per day causes a drop in the academic achievement of students at the middle school level. B: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at Saffi. C: An increase in the time spent on Facebook per day causes a drop in the academic achievement of students at Saffi. D: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at the middle school level.

	🧐 Question	🔧 Skill
	Medium Hiring Developer Skewed Data Graph	3 mins Data Analysis	Try practice test
Two companies A and B hired developers from the year 2001 to 2005. The given bar graph shows the hiring details. Now select the statements that are true based on the given details. A: The data given for Company A is skewed to the left. B: The data given for Company B is skewed to the right. C: The data given for Company A is skewed to the right. D: For Company B, mean and mode are equal. E: For Company B, mean is equal to median but less than mode. F: For Company A, median is less than mode but greater than mean.
	Medium Negative correlation	2 mins Data Analysis	Try practice test
Saffi, one of the popular schools in San Francisco did a school wide study of the students in middle school. The study found that there is a negative correlation between the time spent on Facebook per day by students and their academic achievement. How can we understand the results of this study? A: An increase in time spent on Facebook per day causes a drop in the academic achievement of students at the middle school level. B: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at Saffi. C: An increase in the time spent on Facebook per day causes a drop in the academic achievement of students at Saffi. D: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at the middle school level.

	🧐 Question	🔧 Skill	💪 Difficulty	⌛ Time
	Hiring Developer Skewed Data Graph	Data Analysis	Medium	3 mins	Try practice test
Two companies A and B hired developers from the year 2001 to 2005. The given bar graph shows the hiring details. Now select the statements that are true based on the given details. A: The data given for Company A is skewed to the left. B: The data given for Company B is skewed to the right. C: The data given for Company A is skewed to the right. D: For Company B, mean and mode are equal. E: For Company B, mean is equal to median but less than mode. F: For Company A, median is less than mode but greater than mean.
	Negative correlation	Data Analysis	Medium	2 mins	Try practice test
Saffi, one of the popular schools in San Francisco did a school wide study of the students in middle school. The study found that there is a negative correlation between the time spent on Facebook per day by students and their academic achievement. How can we understand the results of this study? A: An increase in time spent on Facebook per day causes a drop in the academic achievement of students at the middle school level. B: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at Saffi. C: An increase in the time spent on Facebook per day causes a drop in the academic achievement of students at Saffi. D: There is an association between an increase in time spent on Facebook per day and the drop in the academic achievement of students at the middle school level.

Reason #4

1200+ customers in 75 countries

Adaface を使用することで、最初の選考プロセスを 75% 以上最適化することができ、採用担当マネージャーと人材獲得チームの両方にとって貴重な時間を同様に解放することができました。

Brandon Lee, 人々の責任者, Love, Bonito

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Reason #5

Designed for elimination, not selection

The most important thing while implementing the pre-employment A/Bテストテスト in your hiring process is that it is an elimination tool, not a selection tool. In other words: you want to use the test to eliminate the candidates who do poorly on the test, not to select the candidates who come out at the top. While they are super valuable, pre-employment tests do not paint the entire picture of a candidate’s abilities, knowledge, and motivations. Multiple easy questions are more predictive of a candidate's ability than fewer hard questions. Harder questions are often "trick" based questions, which do not provide any meaningful signal about the candidate's skillset.

Science behind Adaface tests

Reason #6

1 click candidate invites

Email invites: You can send candidates an email invite to the A/Bテストテスト from your dashboard by entering their email address.

Public link: You can create a public link for each test that you can share with candidates.

API or integrations: You can invite candidates directly from your ATS by using our pre-built integrations with popular ATS systems or building a custom integration with your in-house ATS.

Reason #7

Detailed scorecards & benchmarks

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Reason #8

High completion rate

Adaface tests are conversational, low-stress, and take just 25-40 mins to complete.

This is why Adaface has the highest test-completion rate (86%), which is more than 2x better than traditional assessments.

Reason #9

Advanced Proctoring

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About the A/B Assessment Test

Why you should use Pre-employment A/B Testing Test?

The A/Bテストテスト makes use of scenario-based questions to test for on-the-job skills as opposed to theoretical knowledge, ensuring that candidates who do well on this screening test have the relavant skills. The questions are designed to covered following on-the-job aspects:

効果的なA/Bテストの設計
データを分析して洞察を引き出す
A/Bテストをアプリケーションに統合します
パフォーマンスのWebアプリケーションのテスト
A/Bテストによる変換の最適化
A/Bテストにおける統計的有意性の理解
テストの競合を特定して解決します
A/Bテストでのユーザーの動作の分析
A/Bテストフレームワークの実装
データ駆動型仮説の開発

Once the test is sent to a candidate, the candidate receives a link in email to take the test. For each candidate, you will receive a detailed report with skills breakdown and benchmarks to shortlist the top candidates from your pool.

What topics are covered in the A/B Testing Test?

A/Bテストの設計
A/Bテストの設計には、パフォーマンスを比較し、データ駆動型の決定を下すために、2つ以上のバリエーションを使用した実験の作成が含まれます。このスキルは、ウェブサイトの設計、ユーザーエクスペリエンス、およびマーケティングキャンペーンを最適化するために重要です。
Full list of covered topics
The actual topics of the questions in the final test will depend on your job description and requirements. However, here's a list of topics you can expect the questions for A/Bテストテスト to be based on.
テストデザイン
サンプルサイズの計算
仮説テスト
コントロールおよび治療グループ
ランダム化
データ収集
統計分析
信頼区間
A/Bテストメトリック
データの視覚化
セグメンテーション
統計的有意性
ヌルおよび代替仮説
電力分析
多変量テスト
実験的バイアス
データ解釈
変換率の最適化
ユーザーエクスペリエンスの最適化
実験計画
倫理的配慮
データクレンジング
A/Bテストプラットフォーム
A/Bテストレポート
A/Bテストの制限
統計サンプリング
データ駆動型の意思決定
回帰分析
相関分析
因子分析
時系列分析
データセグメンテーション
統計的推論
データ操作
統計モデル
データ駆動型の洞察
調査デザイン
データ収集ツール
統計的仮説
データ分析手法
データ検証
データ視覚化ツール
変換率分析
統計的有意性テスト
データ駆動型の意思決定
実験制御
統計テスト
コホート分析
ユーザーの動作分析
分析ツール
データ分析ワークフロー
統計ソフトウェアツール
A/Bテストの実装
データ駆動型マーケティング
データ駆動型の最適化
A/Bテストベストプラクティス
データ分析スキル

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What roles can I use the A/B Testing Test for?

データアナリスト
マーケティングアナリスト
プロダクトマネージャー
ビジネスアナリスト
データサイエンティスト

How is the A/B Testing Test customized for senior candidates?

For intermediate/ experienced candidates, we customize the assessment questions to include advanced topics and increase the difficulty level of the questions. This might include adding questions on topics like

さまざまなユーザーセグメントの実験の設計
データ分析で統計的方法を使用します
大規模なデータセットでA/Bテストを実行します
A/Bテストのベストプラクティスの実装
A/Bテストでのユーザーエクスペリエンスの評価
A/Bテストの結果を正確に解釈します
効果的なテストのバリエーションを作成します
テスト期間とサンプルサイズを最適化します
A/Bテストの監視リアルタイム
実用的な推奨事項を提供します

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サンプルスコアカードを表示します

採用担当者は、パネル面接中に尋ねる専門的な質問を通じて、どの候補者がより良いスコアを持っているかを判断し、スコアがそれほど高くない候補者と区別できると感じました。彼らです非常に満足 Adaface のスクリーニングで最終候補者リストに選ばれた候補者の質を重視します。

85%

スクリーニング時間の短縮

完全なケーススタディを表示します

A/B Online Test よくある質問

複数のスキルを1つのカスタム評価に組み合わせることはできますか？

そのとおり。カスタム評価は、職務内容に基づいて設定され、指定したすべての必須スキルに関する質問が含まれます。

アンチチートまたは監督の機能はありますか？

次のアンチチート機能があります。

グーグル不可能な質問
IP監督
Webの提案
ウェブカメラの監督
盗作の検出
安全なブラウザ

[プロクチャリング機能]（https://www.adaface.com/proctoring）の詳細をご覧ください。

テストスコアを解釈するにはどうすればよいですか？

留意すべき主なことは、評価が選択ツールではなく排除ツールであることです。スキル評価が最適化され、技術的にその役割の資格がない候補者を排除するのに役立ちます。これは、役割の最良の候補者を見つけるのに役立つために最適化されていません。したがって、評価を使用する理想的な方法は、しきい値スコア（通常は55％、ベンチマークを支援します）を決定し、インタビューの次のラウンドのしきい値を超えてスコアを上回るすべての候補者を招待することです。